阅读说明：本技术 数字体验发布技术以及用于辅助治疗睡眠类疾病的声光方法 (Digital experience publishing technology and acousto-optic method for assisting in treating sleep diseases ) 是由 张发宝 李欣梅 于 2021-08-31 设计创作，主要内容包括：本发明涉及声光体验发布技术领域,在本发明的一个实施例中提出一种由软件定义并发布数字化体验的方法,包括：向分别关联于对应使用者的终端电子装置发送第一数据,其中,发送至每个终端电子装置的第一数据,指示要通过终端电子装置提供给对应使用者的数字化体验的至少一个特征；追踪由使用者执行的并且与使用所述终端电子装置提供的所述数字化体验相关联的反应；确定对使用者的所述数字化体验的调整,该调整包括根据各个使用者的追踪的反应而针对不同使用者的不同的调整；以及,根据所确定的调整,将第二数据发送到终端电子装置,所述第二数据用于根据为使用者确定的对应调整,指示所述终端电子装置向各自的使用者提供经过调整的所述数字化体验。(The invention relates to the technical field of sound and light experience release, and provides a method for defining and releasing digital experience by software in one embodiment of the invention, which comprises the following steps: transmitting first data to terminal electronic devices respectively associated with corresponding users, wherein the first data transmitted to each terminal electronic device indicates at least one characteristic of a digitized experience to be provided to the corresponding user by the terminal electronic device; tracking a reaction performed by a user and associated with the digitized experience provided using the terminal electronic device; determining adjustments to the digitized experience for the user, the adjustments including different adjustments for different users according to the tracked responses of the respective users; and sending second data to the terminal electronic device in accordance with the determined adjustment, the second data being for instructing the terminal electronic device to provide the adjusted digitizing experience to the respective user in accordance with the corresponding adjustment determined for the user.)

1. A method for defining and publishing a digitized experience by software, comprising: transmitting first data to terminal electronic devices respectively associated with corresponding users, wherein the first data transmitted to each terminal electronic device indicates at least one characteristic of a digitized experience to be provided to the corresponding user by the terminal electronic device;

tracking a reaction performed by a user and associated with the digitized experience provided using the terminal electronic device;

determining adjustments to the digitized experience for the user, the adjustments including different adjustments for different users according to the tracked responses of the respective users; and the number of the first and second groups,

sending second data to the terminal electronic device based on the determined adjustment, the second data being for instructing the terminal electronic device to provide the adjusted digitizing experience to the respective user based on the corresponding adjustment determined for the user.

2. The method of claim 1, wherein the reaction associated with the digitized experience includes an action performed by a user; and the number of the first and second groups,

the step of tracking the behavior performed by the user further comprises:

receiving data indicative of input to an application running on a respective terminal electronic device;

data indicating respective behavior patterns of the user in response to the contents displayed by the corresponding terminal electronic device is stored.

3. The method of claim 1, wherein the reaction associated with the digitized experience comprises: a) an active input or a passive input by a user of an application associated with the digital experience; and/or, b) user behavior independent/separate from providing input to the terminal electronic device; wherein the passive input comprises the eye movement speed of the user or the parameters of the body movement of the user collected by an environment sensor where the user is located, and the environment sensor comprises a sensor embedded in a mattress; and

the determining the adjustment includes determining the adjustment based on the user's performance relative to the goals of the respective user.

4. The method of claim 3, wherein the goal is for a group of users and is customized for each user within the group.

5. The method of claim 4, wherein the digitizing experience occurs by a handheld/wearable acousto-optic device of the user; the acousto-optic device includes a speaker, and adjusting the digitized experience includes increasing a weight of pink noise in an acousto-optic stimulus issued by the LED light source and/or the speaker.

6. The method of claim 5, wherein determining the adjustment comprises: determining at least one parameter according to the reaction of each user, wherein the at least one parameter is used for driving the acousto-optic equipment to distribute digital experience to the users.

7. The method of claim 6, wherein the acousto-optic device comprises a user's cell phone and/or head wearable apparatus;

the head-wearable device comprises a sensor distributed over a plurality of in vitro mapped regions of a user's head, the sensor configured to acquire electrical brain signals in a different plurality of regions of a user's cerebral cortex, respectively, through the plurality of in vitro mapped regions, the method further comprising the steps of:

acquiring brain wave intensities in respective regions of the plurality of regions by the sensor,

calculating a current first gravity center position of brain waves of the cerebral cortex according to the brain wave intensities of the plurality of areas;

comparing a) the current first barycentric location with b) a second barycentric location, and adjusting the digitized experience to produce different acousto-optic excitations according to the difference between a) and b), so as to make the first barycentric location approach to the second barycentric location, wherein the second barycentric location corresponds to an average of the brain wave barycenters of the cerebral cortex of healthy population samples;

visually presenting information of the first center of gravity position, the second center of gravity position and a change track of the first center of gravity position along with the adjustment of the digital experience of the user to the user of the terminal electronic device.

8. The method of claim 7, wherein the at least one parameter is used to set a segment of a program that provides a digitized experience to a user;

the at least one parameter sets a position for a user in a predetermined sequence of digitized experience elements;

the at least one parameter is indicative of a level or severity of a digitized experience to be provided.

9. The method of claim 7, wherein the digitized experience comprises an electronic game; and

the tracking behavior comprises: tracking the performance of a user in a game, wherein the performance comprises the interaction speed and the interaction accuracy of the user aiming at the game;

the parameters are used to set a goal or difficulty of activation associated with the one or more digital experiences;

the user has a sleep disorder and the digitized experience is a digital prescription for the sleep disorder issued to the user based on the sound and light device.

10. A computer-readable medium, in which instructions are stored, which instructions, when executed by a processor in the electronic device, perform the method of any one of claims 1-9.

11. An electronic device comprising one or more processors and the computer-readable medium of claim 10.

Technical Field

The invention relates to a digital experience publishing technology, in particular to an acousto-optic experience publishing technology for assisting in treating sleep diseases.

Background

In modern society, the pace of human life and work is increasing, competition is becoming more intense, and a series of sub-health states and related complications caused by sleep are attracting great attention with the increasing of external environment and internal stress. Along with the improvement of economic living standard and the improvement of self health consciousness of people, the requirement standard of people on health is continuously improved, and people hope to be capable of obtaining early warning before diseases appear, so that the people can know the self health condition more perfectly.

Compared with the 2014 Chinese sleep index report issued by the Chinese physician Association, the 2015 Chinese sleep index report shows that although the average sleep score of the country in 2015 is improved compared with that of the country in 2014, the number of patients with insomnia, particularly patients with severe insomnia, is greatly increased.

At present, the number of sleep-related diseases reaches 84, wherein sleep apnea syndrome (accounting for 70% of sleep diseases, patients suffering from sleep apnea syndrome have airway collapse and induce apnea events during sleep, and the main cause of the reduction of blood oxygen saturation during sleep is sleep hypoxia.

Many sleep researchers believe that the current medical community lacks a systematic understanding of sleep function and the pathological mechanisms induced during sleep. Many diseases occur during the day, but the time of induction is at night and is very closely linked to the abnormal sleep at night. For example, many hypertensive disorders are caused by sleep apnea syndrome, which is characterized by a period of one night sleep, in which the blood pressure does not drop, but is higher than before, so that more severe cerebrovascular disease is induced. If the sleep apnea is cured in time. Hypertension can be controlled and even cured. A recent study has shown that some cardiovascular and cerebrovascular diseases, erythrocytosis, endocrine dyscrasia diseases and some lipogenesis rapid metabolic dysfunctions are closely related to abnormal sleep.

The sleep quality has important influence on the health of human body and the recovery of patients. Poor sleep can affect the physical and mental health and work efficiency of people.

Sleep is an important physiological process of a human body, and poor sleep quality and related sleep disorders easily cause the adverse effects of organism immunity reduction, cell life attenuation, nervous system disorder and the like. In addition, the quality of sleep is closely related to the recovery of the patient. Therefore, the monitoring of sleep has important value in the fields of medicine and the like.

At present, a polysomnography monitoring system is mostly adopted for sleep quality detection in medical treatment, the detection data is accurate, but the operation is complicated in use, too many wearing parts are needed, and discomfort is easily caused. Some intelligent bracelets capable of detecting sleep are also available in the market, but most bracelets are judged through an ACC sensor, the bracelet is considered to sleep if the bracelet is not moved for a long time, a shallow sleep if the bracelet is occasionally shaken, a deep sleep if the bracelet is always moved, detection data are few, and judgment is not scientific.

In addition, in the prior art, sleep monitoring is mainly used, active sleep intervention is lacked, and particularly, a method for improving sleep quality by intervening sleep through electronic and program means is used.

Electroencephalography (EEG) is a general reflection of electrophysiological activity of brain neurons on the surface of the cerebral cortex or scalp. The electroencephalogram signals contain a large amount of physiological and disease information, and in the aspect of clinical medicine, electroencephalogram signal processing not only can provide diagnosis basis for certain brain diseases, but also provides effective treatment means for certain brain diseases. In engineering applications, people also try to realize a brain-computer interface (BCI) by using electroencephalogram signals, and achieve a certain control purpose by effectively extracting and classifying the electroencephalogram signals by using the difference of electroencephalograms of people on different senses, motions or cognitive activities. However, because the electroencephalogram signal is a non-stationary random signal without ergodicity and the background noise is strong, the analysis and the processing of the electroencephalogram signal are very attractive and are a research subject with considerable difficulty.

Since 1932 Dietch first performed EEG analysis by Fourier transform, the classical methods of electroencephalogram analysis such as frequency domain analysis and time domain analysis were introduced successively in EEG analysis. In recent years, wavelet analysis, matching tracking methods, neural network analysis, chaos analysis and other methods and various analysis methods are organically combined in electroencephalogram analysis, and development of electroencephalogram analysis methods is strongly promoted.

At present, a sleep therapist mainly manages and intervenes an insomniac in a manual mode, and the specific intervention steps comprise:

(1) the method comprises the following steps of (1) collecting the sleep condition of an insomniac in a mode of inquiring, filling a sleep condition table by the insomniac, and the like;

according to the sleeping condition and the sleeping requirement of the insomnia person, a reasonable sleeping target is formulated, and the method specifically comprises the following steps: the time of getting up, falling asleep, getting on bed, etc.;

(2) informing the sleepy target to an insomniac, arranging execution by the insomniac, and recording the actual execution condition;

(3) the sleep therapist gives written reading materials and the like through oral propaganda and education to the insomnia person to improve the influence on the sleep quality caused by poor sleep habits or unnecessary psychological pressure caused by wrong cognition;

(4) periodically interviewing the insomnia people and making adjustments according to the execution condition of the recent sleep target as required.

These intervention steps are performed manually, lack the basis for standardized execution, and moreover lack technical support in the relevant scientific field: due to the fact that basic research related to the fields of preventive medicine and health promotion is not enough, the sleep monitoring product objectively analyzes various collected monitoring data on the surface, physiological significance and human health symptoms of various monitoring indexes and data indications cannot be deeply understood, and the health assessment and management value in the sleep monitoring product cannot be deeply mined.

Disclosure of Invention

Based on the above situation, it would be beneficial to be able to improve the sleep quality in a targeted and personalized manner in an electronic manner.

If the real-time and high-dynamic nerve-level digital interaction can be carried out on a sleeping object, the nervous system of the object is influenced and stabilized, and the improvement of the sleeping quality of the object is beneficial.

In another embodiment of the present application, there is provided a method for software definition and distribution of a digital experience, comprising: transmitting first data to terminal electronic devices respectively associated with corresponding users, wherein the first data transmitted to each terminal electronic device indicates at least one characteristic of a digitized experience to be provided to the corresponding user by the terminal electronic device;

tracking a reaction performed by a user and associated with a digitized experience provided using a terminal electronic device;

determining adjustments to the user's digitized experience, including different adjustments for different users based on tracked responses of each user; and transmitting second data to the terminal electronic device in accordance with the determined adjustment, the second data being for causing the terminal electronic device to provide a digitized experience to the respective user in accordance with the corresponding adjustment determined for the user.

Optionally, in some embodiments, the reaction associated with the digitized experience includes an action performed by the user; and the number of the first and second groups,

the step of tracking the behavior performed by the user further comprises:

receiving data indicative of input to an application running on a respective terminal electronic device;

data indicating respective behavior patterns of the user in response to the contents displayed by the corresponding terminal electronic device is stored.

Optionally, in some embodiments, the reaction associated with the digital experience comprises: a) a user input of an application associated with the digital experience; and/or, b) user behavior separate from providing input to the terminal electronic device; and

the determining the adjustment includes determining the adjustment based on the user's performance relative to the goals of the respective user.

Optionally, in some embodiments, the target is for a group of users and the settings are customized for each user within the group.

Optionally, in some embodiments, the digitizing experience occurs by a handheld/wearable acousto-optic device of the user; the acousto-optic device comprises an LED light source and/or a speaker.

Optionally, in some embodiments, determining the adjustment comprises: determining at least one parameter according to the reaction of each user, wherein the at least one parameter is used for driving the acousto-optic equipment to generate digital experience interaction with the user.

Optionally, in some embodiments, the acousto-optic device comprises a user's cell phone and/or head wearable apparatus;

the head-wearable device comprises a sensor distributed over a plurality of in vitro mapped regions of a user's head, the sensor configured to acquire electrical brain signals in a different plurality of regions of a user's cerebral cortex, respectively, through the plurality of in vitro mapped regions, the method further comprising the steps of:

the brain wave intensity in each area is respectively obtained through a sensor,

calculating a current first gravity center position of brain waves of the cerebral cortex according to brain wave intensities of a plurality of areas;

comparing a) the current first barycentric location with b) a second barycentric location of brain waves of the cerebral cortex in historical sleep data, and adjusting the digitized experience according to the difference between a) and b) to generate different acousto-optic stimuli to approximate the first barycentric location to the second barycentric location, wherein the second barycentric location corresponds to an average sampled value of healthy population samples.

Optionally, in some embodiments, the at least one parameter is used to set a segment of a program that provides a digitized experience to a user;

the at least one parameter sets a position for a user in a predetermined sequence of digitized experience elements;

the at least one parameter is indicative of a level or severity of a digitized experience to be provided.

Optionally, in some embodiments, the digital experience comprises an electronic game; and

the tracking behavior comprises: tracking the performance of a user in a game, wherein the performance comprises the interaction speed and the interaction accuracy of the user aiming at the game;

the parameters are used to set a goal or difficulty of activation associated with the one or more digital experiences;

the user has a sleep disorder and the digitized experience is a digital prescription for the sleep disorder issued to the user based on the sound and light device.

Optionally, in some embodiments, the at least one parameter sets a segment of a program for providing a digitized experience to a user;

the at least one parameter sets a position for a user in a predetermined sequence of digitized experience elements (elements);

the at least one parameter is indicative of a level or intensity of the digitized experience to be provided.

Optionally, in some embodiments, the digital experience comprises an electronic game; and

the tracking behavior comprises: tracking the performance of the user in the game;

the parameter sets a goal or a difficulty of activation associated with the one or more digital experiences. In another embodiment of the present application, a computer-readable medium is provided, wherein the readable medium stores instructions that, when executed, perform the method of any of the other embodiments of the present application. A processor in the electronic device is provided, which includes a computer readable medium and a processor, wherein the readable medium stores instructions that, when executed by the processor, perform the method in any other embodiment of the present application.

In another embodiment of the present application, there is also provided a method for defining acousto-optic digital interaction for sleep-related diseases based on an application program, comprising: providing digital experience program data to instruct the electronic device to present the interaction of the digital interaction program to a user of the electronic device; acquiring drug information for a user characterizing an electronic device; generating tracking information according to the parameters of the digital experience digital interaction program of the user, wherein the tracking information represents the change of the parameters of the digital experience digital interaction program distributed to the user along with time, and the parameters of the digital experience express the digital interaction program of the digital experience in a working state or represent the intensity of an interaction effect generated by the digital experience digital interaction program; acquiring user data acquired for a user of the electronic device during a time period in which the electronic device is used to provide a digital experience digital interaction program; analyzing the user's tracking information, the user data and the user's drug information to determine the extent to which different digital experience-interactive program parameters may reduce the likelihood or severity of the following adverse reactions: a medication to the user; generating, by the at least one computer, association data specifying at least one side effect of the at least one drug, based on the analysis, at least one tracked digital experience-digital interaction program parameter, pre-estimating the at least one tracked digital experience-digital interaction program parameter based on the analysis of the user tracking information, the user data of the user, and the drug information of the user to generate an interaction via the electronic device to reduce the at least one side effect; receiving prescription data characterized by a first user of the first electronic device: selecting at least one digital experience digital interactive program parameter to enable or tune a first digital experience digital interactive program to provide interaction to the first user according to the associated data; and sending data to the electronic device of the first user that causes the first electronic device of the first user to interact with the first user in accordance with the characterization of the first digital experience digital interaction program.

Optionally, the method in some embodiments further comprises: upon receiving data characterizing a drug used by a first user of the first electronic device; determining at least one desired effect of using the drug; selecting at least one digital experience digital interactive program parameter for the first user by using the generated association data to identify a digital experience digital interactive program parameter associated with at least one desired effect of the use of the pharmaceutical product; and sending data enabling the first electronic device to interact with the first user to the first electronic device of the first user according to the selected at least one digital experience digital interaction program parameter.

Optionally, the method in some embodiments further comprises changing a program state of the digital experience digital interactive program for the first user according to a score characterizing an association between the at least one pre-estimated effect and digital experience digital interactive program parameters of the digital experience digital interactive program.

Optionally, the method in some embodiments further comprises: acquiring genetic data of a first user; and determining a pre-estimated likelihood or pre-estimated severity of the first user's efficacy of the medication based on the accessed genetic data of the first user.

Optionally, the method in some embodiments further comprises: accessing drug genomic information, the data indicating an association between at least one gene and drug metabolism in an individual having the at least one gene; and wherein determining the pre-estimated likelihood or pre-estimated severity of the effect of the drug is further based on the drug genomic information.

Optionally, in the method in some embodiments, the digital experience digital interactive program parameters include parameters characterizing: and the digital experience digital interactive program works.

Optionally, in the method of some embodiments, at least one side effect of using the drug experienced by the first user is identified; and selecting at least one digital experience digital interactive program parameter for the first user by using the generated association data to identify digital experience digital interactive program parameters associated with at least one side effect of using the drug; and sending data enabling the first electronic device to interact with the first user to the first electronic device of the first user according to the selected at least one digital experience digital interaction program parameter.

Optionally, in the method in some embodiments, generating the association comprises: learning, by the at least one computer, an association between the digitally experienced digitally interactive program parameter amount and the effect of the pharmaceutical product based on the tracked digitally experienced digitally interactive program parameter amount and the user data.

Optionally, in methods of some embodiments, generating the association data comprises determining at least one score characterizing a correlation of at least one digitized experience digital interactive program with a first side effect of at least one drug,

the step of using the generated association data to set parameters for a digital interactive experience program provided using at least one electronic device includes: at least one digitized experience digital interactive program is selected for a first user determined or pre-estimated to experience a first side effect based on at least one relevance score. Optionally, at least one drug in the methods of some embodiments is an oncology drug.

Optionally, in a method in some embodiments, using the generated association data to set parameters for a digital interactive experience program provided using at least one electronic device, comprises: receiving first user-specific data characterizing a first electronic device; receiving a physiological parameter of a first user; selecting at least one digital experience digital interactive program parameter for the first user according to the associated data, the first user-specific physiological parameters and the first user; and sending data enabling the first electronic device to interact with the first user to the first electronic device of the first user according to the selected at least one digital experience digital interaction program parameter.

Optionally, the method in some embodiments further comprises determining, for the first drug, a score characterizing: the likelihood that administration of the first medication will produce the first effect; the percentage of people who take the first medication and produce the first effect; the severity of the first effect; or an average measure of the severity of the first effect. Optionally, in the method in some embodiments, using the generated association data to set the parameters for the digital interactive experience program provided using at least one electronic device comprises: at least one is set using the association data and a characterization of the first medication taken by the first user. At least one parameter of the digital interactive experience program for the first user after the first user no longer takes the first medication.

Optionally, in the method in some embodiments, the step of using the generated association data to set the parameters for the digital experience digital interaction program provided using at least one electronic device comprises: upon a first user activation, suspending (pending) stops or replaces at least one parameter of the digital interactive experience program. A drug record characterizing at least one drug taken by the first user.

Optionally, the method in some embodiments further comprises generating drug genomic information from (i) data characterizing the inherited characteristic of the individual and (ii) user data of the individual, the drug genomic information characterizing an association between the first inherited characteristic and the drug effect, the individual data comprising evaluation data and/or sensor data.

Optionally, in the method in some embodiments, the user data includes: health condition of the user and/or feedback to investigate the user; and/or user input to the application; and/or sensor data from the electronic device, and/or other electronic equipment associated with the user. Optionally, in the method in some embodiments, the digital experience digital interactive program parameters include at least one parameter value, which characterizes which digital experience digital interactive program is activated for the user of the electronic device.

Optionally, in the method in some embodiments, the tracked digital experience digital interactive program parameter includes a state or configuration value representing the corresponding digital experience digital interactive program.

Optionally, in the method of some embodiments, the tracked digital experience digital interactive program parameter includes at least one configuration that sets how the corresponding digital experience digital interactive program interacts with the user.

Optionally, in the method in some embodiments, the tracked digital experience digital interactive program parameters include at least one configuration that directs how the corresponding digital experience digital interactive program operates.

Optionally, in the method in some embodiments, at least one of the tracked digital experience digital interaction program parameters specifies a severity of an interaction or a level of an interaction of the digital experience digital interaction program.

Optionally, in the method of some embodiments, the association data specifies, for each of a plurality of side effects of the pharmaceutical product, at least one digitized experience digital interactive program parameter that is predicted to reduce the side effect.

Optionally, in the method of some embodiments, the drug is a current drug prescribed for the first user. Wherein the first digital experience digital interactive program is selected based on the effect of the medication experienced by the first user or a future potential effect of the medication that has not been experienced by the first user.

There is also provided in another embodiment of the present application a system, comprising: one or more computers; and at least one computer-readable medium storing instructions that, when executed, cause the one or more computers to: providing, by the at least one computer and to the electronic device, data that causes the electronic device to present interactions of the digitized experience digital interaction program to respective users of the electronic device; acquiring drug information for a user characterizing an electronic device; tracking the digital experience digital interactive program parameters of a user of the electronic device to generate tracking information, wherein the tracking information represents the change of the digital experience digital interactive program parameters distributed to the user along with the change of time, and at least one digital experience digital interactive program parameter expresses which digital experience digital interactive programs are in working states or represents the intensity of interactive effects provided by the digital experience digital interactive programs; acquiring user data acquired for a user of the electronic device during a time period in which the electronic device is used to provide a digital experience digital interaction program; analyzing the user tracking information, the user data of the user and the drug information of the user to determine the extent to which the different digital experience-based interactive program parameters reduce the likelihood or severity of the following adverse reactions: a medication to the user; generating, by the at least one computer, association data specifying at least one side effect of the at least one drug, based on the analysis, at least one tracked digital experience-digital interaction program parameter, pre-estimating the at least one tracked digital experience-digital interaction program parameter based on the analysis of the user tracking information, the user data of the user, and the drug information of the user to generate an interaction via the electronic device to reduce the at least one side effect; receiving prescription data characterized by a first user of the first electronic device: selecting at least one digital experience digital interactive program parameter to enable or tune a first digital experience digital interactive program to provide interaction to the first user according to the associated data; and sending data to the electronic device of the first user that causes the first electronic device of the first user to interact with the first user in accordance with the characterization of the first digital experience digital interaction program.

Optionally, in some embodiments, the operations comprise: upon receiving data characterizing a drug used by a first user of the first electronic device; identifying at least one desired effect of using the drug that has not been reported by the first user: selecting at least one digital experience digital interactive program parameter for the first user by using the generated association data to identify a digital experience digital interactive program parameter associated with at least one desired effect of the use of the pharmaceutical product; and sending data enabling the first electronic device to interact with the first user to the first electronic device of the first user according to the selected at least one digital experience digital interaction program parameter.

Optionally, the system of some embodiments, further comprising changing a program state of the digital experience digital interaction program for the first user according to a score characterizing an association between the at least one pre-estimated effect and digital experience digital interaction program parameters of the digital experience digital interaction program.

Yet another embodiment of the present application provides a non-transitory computer-readable medium storing instructions that, when executed, cause the one or more computers to: providing, by the at least one computer and to the electronic device, data that causes the electronic device to present interactions of the digitized experience digital interaction program to respective users of the electronic device; acquiring drug information for a user characterizing an electronic device; tracking, by at least one computer, digitized experience digital interactive program parameters for a user of an electronic device to generate tracking information characterizing changes in digitized experience digital interactive program parameters assigned to the user over time, wherein the digitized experience digital interactive program parameters include settings for the electronic device. A digital experience digital interaction program for determining interaction effects to be presented to a user of the electronic device; acquiring user data acquired for a user of the electronic device during a time period in which the electronic device is used to provide a digital experience digital interaction program; analyzing the user tracking information, the user data of the user and the drug information of the user to determine the extent to which the different digital experience-based interactive program parameters reduce the likelihood or severity of the following adverse reactions: a medication to the user; generating, by the at least one computer, association data specifying at least one side effect of the at least one drug, based on the analysis, at least one tracked digital experience-digital interaction program parameter, pre-estimating the at least one tracked digital experience-digital interaction program parameter based on the analysis of the user tracking information, the user data of the user, and the drug information of the user to generate an interaction via the electronic device to reduce the at least one side effect; receiving prescription data characterized by a first user of the first electronic device: selecting at least one digital experience digital interactive program parameter to enable or tune a first digital experience digital interactive program to provide interaction to the first user according to the associated data; and sending data to the electronic device of the first user that causes the first electronic device of the first user to interact with the first user in accordance with the characterization of the first digital experience digital interaction program.

There is also provided in another embodiment of the present application, a method performed by at least one computer, the method comprising: identifying, by at least one computer, a drug to be taken by a user of the electronic device; accessing, by the at least one computer, data associating the digital experience digital interactive program settings with the drug effects, the digital experience digital interactive program settings selected based on tracking information characterizing the user's taking of the drug and settings of the digital experience digital interactive program used by the user; selecting at least one digital experience digital interaction program setting to apply the at least one digital experience digital interaction program setting to a user for customizing the digital experience digital interaction delivered to the user to provide an interaction effect on the electronic device during a period of time that the user takes the medicine, thereby reducing or avoiding side effects of the medicine, according to the medicine taken by the user and data associating the digital experience digital interaction program setting with a medicine effect; customizing the digital experience digital interaction provided to the user by applying the selected at least one digital experience digital interaction program setting for the user; and transmitting, by the at least one computer and to the user's electronic device, data for the user's electronic device to interact with the user, based on the selected at least one digitized experience digital interaction program setting, to provide for reduced or avoided side effects of the interactive pharmaceutical product.

Optionally, in some embodiments, applying the selected at least one digital experience digital interactive program setting comprises: updating the care plan for the user to include using a set of digital experience digital interactive programs specified by the selected at least one digital experience digital interactive program setting.

Optionally, the method of some embodiments further comprises: tuning a medical treatment delivered to a user with the digitally experienced digital interactive agent by data sent to the electronic device by the at least one computer.

Optionally, the method of some embodiments further comprises determining a pre-estimated effect of a drug taken by a user of the electronic device, wherein the at least one digital experience digital interactive program setting to be applied to the user is selected in accordance with the pre-estimated effect.

Optionally, the method of some embodiments further comprises: receiving data characterizing that a user of the electronic device experiences a side effect of a medication being taken by the user of the electronic device, wherein the at least one digital experience digital interactive program setting is selected in accordance with the application. Data representing side effects.

Optionally, in the method of some embodiments, the digital experience digital interactive program setting includes a parameter value characterizing a program state of the digital experience digital interactive program or whether the digital experience digital interactive program is in an operating state.

Optionally, in the method of some embodiments, the digital experience digital interactive program setting includes a status or configuration value representing the corresponding digital experience digital interactive program.

Optionally, in the method of some embodiments, at least one of the digital experience digital interaction program settings specifies a level of intensity or interaction effect of the digital experience digital interaction program for providing to the user.

Optionally, in the method of some embodiments, the setting the digital experience digital interaction program with data associated with the drug effect comprises: associating data specifying, for each of a plurality of side effects of the pharmaceutical product, at least one digitized experience digital interactive program setting that is projected to reduce the side effect.

Optionally, the method of some embodiments further comprises: using the data associating the digital experience digital interaction program settings with the drug actions of the first user, the user is set with settings for at least one digital experience digital interaction program after the user stops taking the first drug.

Optionally, the method of some embodiments further comprises: accessing genetic data for a user of the electronic device; and determining a pre-estimated likelihood or a pre-estimated severity of the effect of the user to take the drug based on the genetic data accessed by the user.

Optionally, the method of some embodiments further comprises: accessing drug genomic information, the data indicating an association between at least one gene and drug metabolism in an individual having the at least one gene; and wherein determining the pre-estimated likelihood or pre-estimated severity of the effect of the drug is further based on the drug genomic information.

There is also provided, in a method of another embodiment of the present application, a system including: one or more computers; and at least one computer-readable medium storing instructions operable when executed to cause the one or more computers to perform operations comprising: identifying, by at least one computer, a drug to be taken by a user of the electronic device; accessing, by the at least one computer, data associating the digital experience digital interactive program settings with the drug effects, the digital experience digital interactive program settings selected based on tracking information characterizing the user's taking of the drug and settings of the digital experience digital interactive program used by the user; selecting at least one digital experience digital interaction program setting to apply the at least one digital experience digital interaction program setting to a user for customizing the digital experience digital interaction delivered to the user to provide an interaction effect on the electronic device during a period of time that the user takes the medicine, thereby reducing or avoiding side effects of the medicine, according to the medicine taken by the user and data associating the digital experience digital interaction program setting with a medicine effect; customizing the digital experience digital interaction provided to the user by applying the selected at least one digital experience digital interaction program setting for the user; and transmitting, by the at least one computer and to the user's electronic device, data for the user's electronic device to interact with the user, based on the selected at least one digitized experience digital interaction program setting, to provide for reduced or avoided side effects of the interactive pharmaceutical product.

Optionally, in the system of some embodiments, applying the selected at least one digital experience digital interactive program setting comprises: updating the care plan for the user to include using a set of digital experience digital interactive programs specified by the selected at least one digital experience digital interactive program setting.

Optionally, the system of some embodiments further comprises: tuning the medical treatment delivered to the user with the digitally experienced digital interactive agent by data sent to the electronic device by the at least one computer.

Optionally, the system of some embodiments further comprises determining a pre-estimated effect of a drug taken by a user of the electronic device, wherein the at least one digital experience digital interactive program setting to be applied to the user is selected according to the pre-estimated effect.

Optionally, the system of some embodiments further comprises: receiving data characterizing that a user of the electronic device experiences a side effect of a medication being taken by the user of the electronic device, wherein the at least one digital experience digital interactive program setting to be applied to the user is selected according to: data representing side effects.

Optionally, in the system of some embodiments, the digital experience digital interactive program setting includes a parameter value characterizing a program state of the digital experience digital interactive program or whether the digital experience digital interactive program is in an operating state.

Optionally, in the system of some embodiments, the digital experience digital interactive program setting includes a state or configuration value representing the corresponding digital experience digital interactive program.

Yet another embodiment of the present application provides a non-transitory computer-readable medium storing instructions that, when executed, are operable to cause one or more computers to perform operations comprising: identifying, by at least one computer, a drug to be taken by a user of the electronic device; accessing, by the at least one computer, data associating the digital experience digital interactive program settings with the drug effects, the digital experience digital interactive program settings selected based on tracking information characterizing the user's taking of the drug and settings of the digital experience digital interactive program used by the user; selecting at least one digital experience digital interaction program setting to apply the at least one digital experience digital interaction program setting to a user for customizing the digital experience digital interaction delivered to the user to provide an interaction effect on the electronic device during a period of time that the user takes the medicine, thereby reducing or avoiding side effects of the medicine, according to the medicine taken by the user and data associating the digital experience digital interaction program setting with a medicine effect; customizing the digital experience digital interaction provided to the user by applying the selected at least one digital experience digital interaction program setting for the user; and transmitting, by the at least one computer and to the user's electronic device, data for the user's electronic device to interact with the user, based on the selected at least one digitized experience digital interaction program setting, to provide for reduced or avoided side effects of the interactive pharmaceutical product.

In some embodiments, an electronic device or system includes a plurality of digital operating programs, each associated with a different aspect of device operation or user demand. Each program may have a corresponding set of rules that specify tasks to be performed when appropriate conditions are met. The system may also use the outputs of these programs and the state of the programs to tune (also referred to as adjust) the nature of the user management plan. The various programs may be interdependent, with different programs having states that are modified by the system based at least in part on the states of other programs. In this manner, programs that are not directly related in subject matter or function to other programs may still affect each other's status (e.g., whether the program is activated and at what level or intensity).

The device management techniques described in this specification provide various advantages over existing management techniques. For example, the present approach allows for individualized management for each device, which may have unique operating characteristics, which may avoid or mitigate the need for maintenance by proactively and dynamically tuning operation according to the device's unique context and state.

Because the operating characteristics of electronic devices may be interrelated or combined together in certain tasks or activities, and a change to one operating characteristic of an electronic device may affect or cause a change to a different operating characteristic, an electronic device management plan may account for the change to the electronic device. The first operating characteristic is implemented by changing a level of the first program in response to a change to the operating characteristic.

The generation of the management plan may be performed automatically by the user, or may be performed in combination (for example, automatically in the case of user input). For example, a set of programming guidelines may be used to generate the management plan, where certain variables may be input by a user. In some examples, the management plan may be automatically generated by applying machine learning techniques. For example, operational data for electronic devices in similar contexts or situations may be collected over time, and observed trends and patterns may be used as learning examples to determine learning states for classifiers, neural networks, or other machine learning models, which may learn to characterize combinations of program states that are appropriate for different situations.

Alternatively, the digitized experience in some embodiments may be considered a prescription for acousto-optic based interactive therapy.

In some embodiments, a method comprises: accessing a drug information database characterizing tumor drugs and their effects; storing a record characterizing a tumor drug currently or previously used by the first user and a current physiological parameter of the first user; evaluating the applicability of the DIE interactive program to the first user according to the record of the first user, comprising: (i) determining a current or desired effect of an oncology drug currently or previously used by a first user; (ii) a score is determined that characterizes an association between the determined effect and the digitized experience digital interactive program.

Other embodiments of these aspects include corresponding systems, apparatus, and computer programs, for executing the acts of the methods, encoded on computer-stored electronic devices. A system of one or more computers may be configured by means of software, firmware, hardware or a combination thereof installed on the system that in operation causes the system to perform operations. The at least one computer program may be configured by means of having instructions which, when executed by the data processing electronics, cause the electronics to perform actions.

In some embodiments of the application, the sound source module and/or the light source module arranged on the cap body issue the acousto-optic experience to the user in a software mode, so that the non-contact intervention and treatment of the physiological indexes of the sleep diseases of the user by the digital prescription are realized. And the digital prescription is adjusted according to the issued acousto-optic experience through the reaction and feedback of the user aiming at the acousto-optic experience, and the adjustment has real-time performance, dynamic performance, individuation/customization.

In some embodiments of the present application, a digital experience provided to a corresponding user (also referred to as a user) by an electronic device used by the user is provided, and the distribution of the digital experience to the user is adjusted according to a reaction associated with the digital experience. Provides 'electronic medicine' based on mobile phone application programs of integrated VR technology for non-invasive independent or auxiliary treatment of chronic diseases, and provides a low-cost convenient replacement therapy for improving or preventing sleep diseases such as sleep disorder. Thus, the user's response to the published digital experience tends towards a normal numerical range, which is the measured average of the relevant physiological indicators of healthy people. The user can be a group suffering from a certain disease with passivated and abnormal nerve reflex, such as sleep-type disease. Of course, it can also be used as a digital therapy for other diseases, for example, to help patients reduce side effects of drugs. The digital experience (digital experience for short) can be regarded as a digital prescription for a certain disease, and is issued by electronic devices such as a mobile phone and a server and experienced by a user (assumed as a patient) of the mobile phone, feedback/reaction (such as input speed of the user, which can reflect indexes such as neural activity ability) of the user can be easily collected and reported to the server by the terminal electronic device held by the user, and the server can adjust the corresponding digital prescription with high dynamics and flexibility according to changes of the indexes/parameters, such as adjusting game progress, game difficulty and game type. Of course, it is assumed here that the digital experience is a game running in a terminal device held by the user. Therefore, the quick collection of the physiological indexes of the user and the quick change of the digital prescription according to the change of the physiological indexes, namely the release content of the digital experience can be realized. The publishing flexibility, the dynamic property and the real-time property of digital experience aiming at a certain specific disease patient are greatly improved. And different customized prescriptions can be very conveniently issued according to different responses of a plurality of users to digital experiences, which is very beneficial for the collective management, treatment and issuing of digital experiences of one patient group. The digital acousto-optic experience of the user release is realized, the collection and timely accurate sleep data are supported, and the data is safe and traceable, so that an electronic sleep image of the user is generated, and effective reference can be provided for artificial treatment when needed. The method is based on the user sleep data acquisition (for example, the user head sensor acquires brain electrical signals of the cerebral cortex in a subarea), and also supports the realization of more personalized and fine sleep target management for the insomnia patients.

Further, in some embodiments, a gridding mode is further adopted to monitor the mapping area of the user cerebral cortex on the body surface, the activity gravity center of the whole cerebral cortex is calculated according to the signal intensity, and the activity gravity center of the cerebral cortex of the user is promoted to gradually trend to the normal position of a healthy population in the sleeping process by adjusting the acousto-optic experience release content of the user in a feedback mode. A visual mode is provided for the measurement and the display of the sleep quality of the user.

The details of at least one embodiment of the subject matter described in this specification are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages of the subject matter will become apparent from the description, the drawings, and the claims.

Drawings

Brief description of the drawingsthe accompanying drawings:

FIG. 1 shows a diagram of an example system for managing electronic devices in one embodiment of the invention.

FIG. 2 illustrates a diagram of an exemplary learning system for managing electronic devices in one embodiment of the invention.

FIG. 3 is a schematic diagram showing the time-varying center of gravity of brain electrical signal distribution in a mapped region of the cerebral cortex according to another embodiment of the present invention;

FIG. 4 is a schematic diagram of a circuit topology of a reputation experience publishing device for performing the method of an embodiment of the present invention.

FIG. 5 is a schematic diagram of a circuit topology of a reputation experience publishing device for performing the method of an embodiment of the present invention.

FIG. 6 is a flowchart illustrating a method for defining and publishing a digital experience from software in accordance with an embodiment of the present invention;

like reference numbers and designations in the various drawings indicate like elements.

Detailed Description

FIG. 1 shows an example of a system for managing electronic devices of an enterprise 101 that includes a plurality of different electronic devices 120a, 120b, and 120c (the three reference numerals may also be referred to generally as 120). Each electronic device 120a, 120b, and 120c is different: with different characteristics and different operating parameters. The electronic device 120 may be, for example, an electronic device in the administrative enterprise 101. The administrative enterprise 101 may include the same type of electronic device, e.g., some electronic devices may be the same model and from the same manufacturer; although these electronic devices have the same model and the same manufacturer, each electronic device may be unique and may have unique characteristics that affect the operation and efficiency of each electronic device. For example, one electronic device mayCan have been used for 9 years and its thickness of the timing belt is different from other electronic devices of that brand and model. In another example, different electronic devices of the same make and model may have been in use for 6 weeks, and their components may require a break-in period. Thus, although electronic devices may have the same general function or role, electronic devices may have different optimal operating conditions and produce different quality products at different speeds. The system 100 generates a dynamic, customized operating plan or management plan for each electronic device. The system 100 includes a server system 110 and an administrator system 130. The server system 110 communicates with each of the other components of the system, such as the electronic devices 120a, 120b, and. Server system 110 also has access to a plurality of data sets, as shown by database 111, program rules 112, and program content 113.

The example in FIG. 1 shows various interactions that may be used to create, tune, and execute management plans. As described above, the system 100 can generate management plans for various electronic devices. Each electronic device may be associated with at least one user. The characteristics or behavior of the user may be taken into account when determining the programs and levels that are valid for a given electronic device. Thus, the management plan may also guide or assist in managing the behavior of the user of the electronic device through the output and interaction of the electronic device when the management plan is applied, not just the direct operation of the electronic device.

For example, the interactions shown in stages (a) to (E) follow the following procedure: creating a management plan for the electronic devices, monitoring the status and requirements of each electronic device, providing instructions and commands, and tuning the management plan for each electronic device. The management plan provided by the system is not merely a description of the desired electronic device performance or operating plan. Rather, the management plan provided by the system 100 is a real-time, interactive, customized service that initiates communication and interaction with the electronic device or user to perform an operational plan that tunes how the electronic device operates. The management plan may involve, among other effects, interactions initiated by the system 110 or a user that alter the performance or operation of the electronic device in at least one aspect. The system 100 may operate in an "always-on" manner, frequently or continuously evaluating the data stream characterizing the current state and context of the electronic device (and thus the user of the electronic device), and providing an estimated future need for the current and/or associated directionally-interactive electronic device and corresponding user.

During stage (A), server 110 generates and provides an administrator portal 132, which may be provided as a web page, a web application, data for a locally executable application of administrator system 130, or in another form. The administrator portal 132 enables an administrator to view the management plan template 134 and select a template for registering a new electronic device (e.g., machine or electronic device). The administrator portal 132 also provides the administrator with controls to modify individual management plan templates 134 and to view and change the management plan that is currently active for any electronic device with which the administrator is assisting.

The administrator portal 132 provides a number of administration plan templates 134 that the administrator may select when registering a new electronic device. In some cases, the templates correspond to different areas or fields that the user wishes to manage. The management plan may be generated as a combination of different digital operation programs. The management plan template 134 may specify a set of programs that are inactive for a given electronic device. Each program has a number of components and illustrates the way they interact with the electronic device. For example, each program may include a plurality of segments that are applicable over different time periods. The program may define the order of the segments or may define a number of different orders. These segments may correspond to fixed length time segments, such as a week or a month, or another fixed or standardized time segment. Alternatively, at least one period may have a variable duration.

Each program has various levels or intensities that are applicable to the program. Different levels may correspond to different levels of demand. In some implementations, different levels of a program may respond to different goals or conditions.

When an electronic device is first registered, the administrative plan template 134 selected by the administrator specifies a default set of programs and corresponding levels for the electronic device. The administrator may manually tune the selection, for example, by adding or deleting programs and increasing or decreasing program levels. In this case, the administrator may specify an initial management plan that satisfies the requirements of the electronic device identification.

Using the interface and tools provided by server 110 through administrator portal 132, an administrator can effectively manage the management plans for a large number of electronic devices. In many cases, after the management plan is initiated, the administrator does not need to further modify or tune the management plan. The server 110 automatically tunes each individual management plan based on a unique set of user inputs and sensor data detected for each electronic device. However, an administrator may view the progress of a single electronic device and, where appropriate, may manually tune the management plan for the electronic device through the administrator portal 132. As the server 110 adjusts the management plan according to the specific situation of each electronic device, different management plans will have different program segments, different program levels, and different activity program combinations. These differences, as well as applying a single operational rule to a unique electronic device data set, provide a unique experience for each user.

During stage (a), the server 110 stores information about each electronic device registered in the system. The server 110 may store information using a data storage subsystem, which may include, for example, directly connected storage (e.g., hard disk drives, solid state drives, etc.), locally connected storage, network connected storage (NAS), at least one database, a Storage Area Network (SAN), a database management system (DBMS), and/or at least one database server or other element. For example, the data storage subsystem may include at least one relational database (e.g., SQL database), at least one object-oriented database, at least one noSQL database (e.g., key-value database, wide-column storage database, etc.), distributed data store, at least one file system, or other data storage system. The data storage subsystem may store data (e.g., status information, sensor data, operational history, etc.) collected from the managed electronic devices. 110 (e.g., current and previous levels for different programs, instructions to the electronic device, source content, and generated content to be sent to the electronic device, etc.). As discussed further below, the server 110 stores data characterizing the current state of the management plan of the electronic device, such as the programs that are active, the level of each program, the segment in which the user is currently located in each program, and so forth. In addition, the server 110 stores history information about the electronic device and its interaction with the application and progress while using the management plan. The server 110 may obtain data from many different sources, including surveys, sensor data, and other data discussed further below. This information may be stored in various databases 111.

The behavior of the server 110 to generate the user's first interface and content (or action) may be retrieved from the storage of the application content 113. The storage 113 may include media, messages and other content that are selectively provided according to the operating rules in the storage 112, and the media, messages and other content are in turn in accordance with a) which programs are in working states, b) which levels of programs are in working states and which segments, and thus the selectively used programs are in working states.

The server 110 provides a set of application data 150 characterizing the active scheme for each device and the levels 120a, 120b, and 120c of each active program.

During stage (C), the server 110 acquires data for each of the respective users registered with the management plan. The server 110 communicates with the electronic device 120 to obtain data for each of the various electronic devices that scroll with the management plan. The server 110 communicates with the electronic devices 120 to obtain contextual information, such as the location of the respective electronic device, the current activity of the electronic device, sensor data, and other data. The server 110 also communicates with third party systems to access data such as electronic device activity and interaction, and even general information such as current news, weather, and other data.

In stage (D), the server 110 applies the individual management plan for each electronic device to the data collected for that electronic device. For example, rules applicable to active segments of an active program are evaluated using contextual information history information and other data. Although different programs may characterize different messages to be provided or different instructions to be presented to the electronic device, the server 110 may integrate content across the various programs.

During stage (E), the server 110 adjusts the state of the program, if appropriate. Server 110 may evaluate various factors to determine whether the set of active programs should change, and whether the level and active segment of each program should change. In some cases, the electronic device may advance through various portions of the program as time passes. The server 110 may detect when there is an appropriate change from one time. Until the next occurrence, and therefore when the applicable rule changes.

The server 110 may include a program status setting unit to evaluate and change the program status in each management plan. Using the program state setting unit, server 110 may evaluate various factors to determine whether the set of active programs should change, and whether the level and active segment of each program should change. In some cases, the electronic device or user may gradually browse through various portions of the program as time passes. The program state setting unit of the server 110 may detect when a transition from one time period or one portion of the program to another time period should occur. Generally, the program state setting unit may include software and/or hardware that accesses data characterizing a current program state of the electronic device or user, evaluates data received from the electronic device or user or other sources, and sets a program state for managing the plan. The result of the evaluation is the electronic device or the user. The program state setting unit may iteratively perform these operations, for example, periodically (e.g., periodically). As another example, the program state setting unit may re-evaluate the program state of the electronic device or the user in response to receiving additional information such as sensor data, user input, data characterizing the operation of the electronic device, or other input. As will be described below in detail with reference to the accompanying drawings,

the server 110 may include an instruction generation unit that generates customized instructions to change the operation of the managed electronic devices according to the updated program state of each electronic device. The instruction generating unit may include at least one software module that accesses an electronic device first or user first program state of the electronic device, determines appropriate rules from the program corresponding to the state, applies the determined rules (e.g., evaluates a subset of the electronic device). Rules of the program to determine which rules satisfy the conditions and triggers) and generate instructions for the electronic device to perform the tasks characterized by the rules. The context information history information and other data may be used to evaluate rules applicable to an activity segment of an activity program.

The instruction generation unit may operate using any of a variety of techniques. For example, the instruction generation unit may determine appropriate program levels, identify content (e.g., media, templates, potential instruction sets, etc.) corresponding to those levels, and then generate customized instructions as selections from the identified content. As another example, the instruction generation unit may filter or narrow content for a first program level to avoid duplication based on a previous history of the electronic device or user (e.g., based on validity of previous instructions, based on current and previous context information of the electronic device or user), the instruction generation unit may access a machine learning model to generate instructions, provide a program state representation of the electronic device or user to the machine learning model, and receive an output of content or types of instructions that may be applicable based on the program state representation. The instruction generation unit may use the output of the machine learning model to retrieve or generate the data elements sent in the custom instruction. As another example, the instruction generation unit may access at least one instruction template and populate the template with elements selected according to an electronic device first or user first program state of the electronic device and current and historical information about the electronic device or the electronic device. The user thereof. The instruction generation unit may use the output of the machine learning model to retrieve or generate the data elements sent in the custom instruction. As another example, the instruction generation unit may access at least one instruction template and populate the template with elements selected according to an electronic device first or user first program state of the electronic device and current and historical information about the electronic device or the electronic device. The user thereof. The instruction generation unit may use the output of the machine learning model to retrieve or generate the data elements sent in the custom instruction. As another example, the instruction generation unit may access at least one instruction template and populate the template with elements selected according to an electronic device first or user first program state of the electronic device and current and historical information about the electronic device or the electronic device. The user thereof.

The server 110 may include a transmission module to transmit the customized instructions to the electronic device. For example, the transmission module may include a network interface controller, such as a LAN adapter, a WAN adapter, a network interface card, or other electronic circuitry (possibly with associated firmware and/or software) configured to communicate using a physical layer and a data link. Layer standards such as ethernet or Wi-Fi. When customized instructions are determined for various electronic apparatuses, the server 110 transmits instructions for causing the electronic apparatuses to change their operations and outputs using a transmission module through a network such as the internet, a local area network, a wide area network, or the like. .

Fig. 2 shows an example management system S2. The management system S2 is an example of a system implemented as a computer program on one or more computers in at least one location (e.g., at least one server) that implements the systems, components, and techniques described below.

The management system S2 selects an operation plan or program schedule to be applied in order to manage the electronic devices in the complex system 100 determined from the learning/feedback data S23. That is, the learning/feedback data S23 received by the management system S2, such as 100 in the complex system of electronic devices in the current programming state S26, 100 in the complex system of electronic devices in the sensed condition, and/or the system of complex devices 100 in the result data S25. In response to the learning/feedback data S23, the management system S2 generates a global operation plan output using the global operation plan neural network S21. In some examples, each observation includes raw sensor data captured by at least one sensor, such as visual data, Inertial Measurement Unit (IMU) readings, and so forth. The learning/feedback data S23 may be 100 specific to the complex system of the first electronic device 120a, 120b, and 120C. In some examples, the learning/feedback data S23 is generally applicable to the complex system 100, allowing the machine learning model of the system S2 to discover and recreate response patterns that transition from one set of required programs and levels to another, more desirable program and level set.

The global operation plan neural network S21 is a neural network for receiving observations in the form of input data (e.g., learning/feedback data S23) and processing the observations in accordance with current values of the observations to generate a global operation plan output. Parameters of the global operation plan neural network S21. The global operational plan output defines a probability distribution 100 for managing electronic devices within a complex system to perform a set of possible actions, e.g., electronic devices 120a, 120b, and 120C. For example, the global operation plan output may include an average behavior vector and a covariance of entries of the average behavior vector. In this example, the global operation plan output includes an average behavior vector including a corresponding entry for each electronic device tool, i.e., a corresponding average spindle speed, and a covariance of the entries of the average behavior vector.

In order to effectively tailor the respective operation plans the first electronic device is responsive to the learning/feedback data S23, the global operation plan neural network S21 of the train of the system S2 is managed to determine trained values S21 of the parameters of the global operation plan neural network. The global operation plan neural network generates operation plans S22a, S22b, and S22C for 120a, 120b, and 120C of each corresponding electronic device. Each operation plan includes a progress of the program status setting of the first electronic device.

Generally, the management system S2 performs multiple iterations of the two-step learning method to learn the global operation plan neural network S21.

Instead of learning directly the parameters of the global operation plan neural network S21, the management system S2 learns the simple operation plan 102a, 102b, or 102c of the first electronic device (e.g., electronic device) 100 using a progressive or trajectory-centric algorithm in a first step of the learning method. The global operation plan neural network S21 is based on the learning/feedback data S23 from the operation plans S22a, S22b, and S22 c. The feedback S23 includes data such as result data S25, current program state S26, sensed conditions and historical data S24.

The result data S25 includes data characterizing the results of applying the operation plan to the respective electronic devices. For example, whether the first operation plan achieves improvement may be recorded as the result data S25. The result data S25 may be generated or collected by the global operation planning neural network S21. In some examples, the result data may be received from the operation plan S22 or the electronic device 120S 25.

The current program state S26 includes data characterizing the state of each program applied to each corresponding electronic device at the time of learning/feedback data S23. The current program state S26 may also include a feature vector representing the corresponding electronic device. For example, the feature vector of the first electronic device may indicate that it has been in use for 8 years and that the battery life is short. Sensed condition S27 includes, for example, data collected by a sensor (e.g., a temperature sensor, a digital scale, an optical sensor, a camera, an inductive sensor, a motion sensor, a microphone, an ultrasonic sensor, etc.). The sensed condition S27 may include an external condition such as temperature, air quality index, speed, direction, etc., or an internal condition of the electronic device. The current program state S26 and sensed conditions may be received from the operational plan S22 or the electronic device 120.

The history data S24 includes history values for various feedbacks, including result data S25, current program state S26, and history values of sensed conditions S27. The global operation plan neural network S21 may collect and store historical data S24 in a storage medium. In some examples, the historical data S24 may be stored in a storage medium by the operation plan S22 or the electronic device 120.

Specifically, for each of these electronic devices 120a, 120b, and 120C, the management system S2 generates a pass selection scheme to manage the operation plan 120 to be applied by the electronic device. The feature vector includes various programs and levels for which, particularly for each electronic device, the management system S2 uses the global operation plan neural network S21 and determines a state-to-state transition or operation plan based on the current operation. Characteristics of each electronic device. The global action plan neural network S21 receives, for example, a feature vector representing the first electronic device. The system may generate an operation plan based on the current values of the parameters of the global operation plan neural network S21. That is, the system may receive a series of observations or input data (e.g., the learn/feedback data S23) and, in response to each observation in the series, process the observation using the global operation planning neural network to generate a planned output in which global operations plan observations according to current values of the variables, and then sample the operations from a distribution defined by the global operation planning output.

The management system S2 may then optimize the respective operation plan S22a, S22b, or S22C for each electronic device 120a, 120b, or 120C. That is, for each electronic device, the management system S2 optimizes the operation plan for the electronic device at the program level and the progress of the program.

In the second step of the learning method, post-optimization operation plans S22a, S22b, and S22c, the management system S2 establishes a learning set using the optimized operation plans for learning complex, high-dimensional global planning patterns under supervision. That is, the management system S2 generates learned data for the global operation plan neural network S21 using the optimized operation plan S22, and learns the global operation plan neural network S21 on the learned data to adjust the current values of the parameters of the global operation plan. The global operation plan neural network S21, for example, uses supervised learning. The management system S2 may learn the global operation planning neural network 120 using only the received observations (e.g., the learning/feedback data S23), and thus, the global operation planning neural network S21 is able to pre-estimate behavior from the learning/feedback data S23. .

The management system S2 can effectively utilize the neural network S21 selection scheme of the global operational plan to manage the applications of these electronic devices 120 one, 120b, and 120c once the neural network S21 of the global operational plan has been learned. In particular, in the case of observations received, the management system S2 may process the observations using the global operation plan neural network S21 to produce a global operation plan output S21 in accordance with learned values of parameters of the global operation plan neural network. The management system S2 may then select a new application or application level to apply to managing the electronic devices 120a, 120b, and 120c in response to the new learning/feedback data S23. For example, if the learning/feedback data S23, first in the electronic device 120C, is received, the global operation planning neural network S21 may process the learning/feedback data S23 and learn globally the entire complex system 100 and apply the behavior trace first in the electronic device 120C.

In some embodiments, the global operation plan neural network S21 includes a convolutional subnetwork (e.g., as an initial processing portion of the network) and a fully connected subnetwork.

The management system S2 may learn learned data on the global operation planning neural network S21 to tune the current values S21 of the parameters of the global operation planning neural network by, in some examples, tuning the fully-connected parameters while keeping the current values of the current value convolution parameters fixed. In some other examples, the management system S2 may learn learned data on the global operation planning neural network S21 to align the current values S21 of the parameters of the global operation planning neural network by aligning current values that fully connect the parameters and the current values convolve the parameters.

In some embodiments, the management system S2 pre-learns the convolutional neural network with proxy gesture detection targets to determine pre-learned values for the convolutional arguments, i.e., before learning the neural network S21 using a two-step approach.

Additionally, in some embodiments, in addition to or instead of pre-learning the convolutional neural network, the management system S2 pre-learns the neural network S21 on learned data generated as a result of a conventional global policy search and performs operation plan optimization on that data. Each of the electronic devices 120a, 120b, and 120 c.

The system may repeatedly perform the learning process until a termination criterion for learning the global operation plan neural network is satisfied to determine learned values of the parameters of the global operation plan neural network. For example, the system may perform the learning process for a period of time until a certain number of iterations of the learning process are performed, or until the global operation plan neural network S21 reaches a threshold level of performance throughout the operation plan.

FIG. 6 is a flowchart illustrating a method for defining and publishing a digital experience by software according to an embodiment of the present invention. The method of this embodiment includes the following four steps. In a first step SP1), a digitized experience issued by the sound source module and/or light source module P23; and transmitting the first data to the terminal electronic devices S109 respectively associated with the corresponding users, wherein the first data transmitted to each terminal electronic device S109 is used for indicating at least one characteristic of the digital experience to be provided to the corresponding user through the terminal electronic device S109, for example, the digital experience is a game application and an acousto-optic signal/information thereof propagated outwards through a display, a loudspeaker and the like, and then the at least one characteristic can be a running speed of the game, an interaction speed with the user and the like.

In a second step SP2), the reactions performed by the user and associated with the digitized experiences published by the acousto-optic experience publication device S109, such as the user' S input speed, eye movement speed (or what can be understood as eye movements during eye movement sleep) etc., are tracked, which may reflect their ability to neural activity, rhythm/rhythm to go into a state of dormancy, etc.

In a third step SP3), adjusting the digitized experience published by the sound source module and/or light source module P23 according to the reaction associated with the digitized experience; through the adjustment and release of the acousto-optic experience, the user can enter the sleep state more quickly, or the user can enter the deep sleep state from shallow sleep more quickly, and a more optimized sleep curve is formed. The adjustment includes different adjustments for different users based on the tracked responses of each user. Thereby, the server connected to the sound and light experience distribution device S109 can realize one-to-many batch management and multi-object synchronous customized sleep intervention.

In a fourth step SP4), second data are sent to the terminal electronic device S109 according to the determined adjustment, the second data being used to instruct the terminal electronic device S109 to provide the adjusted digitizing experience to the respective user according to the corresponding adjustment determined for the user. The sound and light experience distribution apparatus is referred to herein or in other embodiments or also as the terminal electronics S109.

Optionally, in some embodiments, the digitized experience includes some acousto-optic stimuli, such as signals/information propagated externally by the gaming application through a display, speakers, and so forth. The reaction associated with the digitized experience includes actions performed by the user, such as the speed of reaction when the user operates the game, the speed of operation of keys associated with the game, speed data of interaction with the game application, and the like. In addition to these active inputs, the reactions associated with the digitized experience may also include some passive inputs including the speed of the user's eye movements or parameters of the user's body movements acquired by the environmental sensors in which the user is located, including sensors embedded in the mattress.

The step of tracking the behavior performed by the user further comprises: data indicative of inputs to applications running on respective acousto-optic experience distribution devices is received, such as receiving user body motion parameters, user eye movement speed parameters, etc. acquired by sensors in the mattress as described above.

The adjustment to the digitized experience in S-ii) comprising determining an adjustment based on the user' S performance relative to the goals of the respective user; wherein the target may be for a group of users and customized for each user within the group.

If the passive input of the user is not as expected, the acousto-optic experience issued by the terminal electronics S109 is adjusted so that the center of gravity position of the brain waves or brain waves embodied in the gridded coordinate system of the user can approach a) the sleep characteristic curve of a healthy population or b) the target center of gravity position of the brain waves along a predetermined sleep curve at a faster speed and rhythm. Adjusting the acousto-optic experience may be, for example, increasing the weight of pink noise in the acousto-optic experience. Because, the inventors found that the pink noise stimulates or boosts the patient's deep sleep. The "Pink Noise" (Pink Noise) sound frequency sounds like a waterfall, specifically inducing Delta vibrations (0.5-4Hz) that characterize dreaminess deep sleep.

Optionally, in the sound-light experience distribution apparatus of some embodiments, the sound source module and/or the light source module P23 includes an LED light source P11 and/or a speaker P22.

Optionally, in some embodiments, determining the adjustment to the digital experience comprises: at least one parameter is determined according to the reaction of each user, and the at least one parameter is used for driving the acousto-optic experience issuing equipment (or simply referred to as acousto-optic equipment) to generate digital experience interaction with the user. For example, adjusting the digitized experience according to the at least one parameter includes: increasing the weight of pink noise in the acousto-optic excitation issued by the LED light source and/or the speaker. Thus, the coordination of the server which is in communication coupling with the acousto-optic experience issuing equipment can lead a plurality of patients with sleep disorder to synchronously obtain benign adjustment, influence and even treatment on different physiological index sets through respective acousto-optic experience issuing equipment. The large-scale customization, one-prescription-for-one-person and one-prescription-for-thousands-of-persons treatment effects of the acousto-optic experience issuing equipment in the embodiments are enhanced, and the method is greatly superior to the prior art, particularly the physiological index intervention method for treating diseases such as sleep disorder mainly by manual participation.

Optionally, in the sound-light experience distribution apparatus of some embodiments, the at least one parameter sets a section of a program for providing a digitized experience to the user; the at least one parameter sets a position for the user in a predetermined sequence of digitized experience elements; the at least one parameter is indicative of a level or intensity of the digitized experience to be provided. For example, the pink noise is a digitalized experience element/acousto-optic stimulation element/acousto-optic experience element, and in the acousto-optic experience distribution equipment, the similar acousto-optic experience element can be sequentially distributed to the outside through the display and the loudspeaker, so that the sleep of the user is influenced and intervened.

The method of software-defined and distributed digital experience in other embodiments may be implemented in a head-wearable device having an internal electrical topology as shown in fig. 5. These wearable devices, as an embedded system S109, with virtual drivers integrated in the stored applications (not shown), can provide a continuous average power output of 1W, which is amplified and then fed to the circuit P66 for driving the light and sound sources.

A control module S11 and a P99 programming key and a display module in the wearable device are connected with a virtual microprocessor S55 to be used as a main control unit of an embedded system S109 and used for signal processing and calculation and timing voice prompt of treatment of a patient, as shown in figure 4, a 40Hz low-frequency pulse signal is output in a standard mode, the main frequency of the processor reaches 168MHZ and comprises an I \ O port and a timer, when the patient manually interrupts the treatment, the microprocessor judges whether the overflow frequency of timer interruption reaches the set frequency, controls the high and low level of the I \ O output to generate a pulse driving signal with adjustable frequency, as the adjustable frequency range is 35-45HZ and the cycle time range is 22.2-28.6ms, the I \ O output voltage direction is inverted after the timer is interrupted, the duty cycle of an output signal is set to be 50%, and thus the time of two times of timer interruption is a cycle time, the frequency of the output signal is changed by controlling the interrupt time of the timer through the keys, the frequency is changed by 0.5Hz when the keys are pressed each time, the current of the output signal of the I \ O port of the control module can reach 10mA, the output voltage can reach 3.6V, and the output signal of the port can be used as the input signal of the signal amplification driving module P66. When the device is used, the output port is controlled by keys of the control modules S11 and P99 to generate one path of virtual driving signals to be used as the input of the signal amplification driving module P66, the signal amplification driving module P66 outputs two paths of driving signals with the same frequency, the two paths of driving signals respectively drive the light source and the sound source to generate light and sound, and a patient adjusts the proper frequency, intensity and audio frequency through the keys of the control modules S11 and P99.

The storage module S66 stores the traceable visual and auditory feedback information therapy log record (timer interrupt, frequency, light intensity, audio adjustment record).

Because the signal is only amplified and converted by the signal amplification driving module, the frequencies of the two generated driving signals are the same, so that the output light and sound resonance frequencies are always kept consistent, and the keys of the control template can change the frequency, light intensity and volume of the light source and the sound source. The acousto-optic signals with the same frequency jointly act on the brain through audition nerves to generate electroencephalogram signals with specific frequency, the initialization frequency is 40Hz in the treatment process, and acousto-optic signal parameters can be adjusted according to the tolerance of a user, feedback/reflection during acousto-optic experience and requirements.

The wearable device is provided with the acousto-optic driving unit to generate acousto-optic excitation signals, so that acousto-optic excitation is carried out on the user through ears and eyes of the user, and the acousto-optic driving unit is in interface with nerves of a human body through the energy of acousto-optic, so that the excitation signals are required to be very sensitive and very dynamic, and can be correspondingly adjusted in real time in response to the reaction/feedback of the human body.

In order to solve the problem, in some embodiments of the present invention, the acousto-optic driving unit is connected to an energy storage device as a buffering unit for electric energy, so that sufficient electric energy storage for the acousto-optic driving unit is always maintained, and the acousto-optic driving unit has great dynamics, i.e., dynamic processing capability for electric energy.

It is contemplated that the wearable device in any of the other embodiments of the present application includes an acousto-optic drive unit, and may further include: the energy storage device is connected with the acousto-optic driving unit; the energy storage device further includes:

a plurality of energy storage components, each of the plurality of energy storage components comprising an anode and a cathode;

a second energy storage assembly; and

a plurality of switching cells, wherein the plurality of switching cells comprises at least two or more poles and wherein:

in a high-level mode of the plurality of switching cells, the first energy storage component and the second energy storage component are coupled in series, an

In a low-level mode of the plurality of switching units, the first energy storage component and the second energy storage component are coupled in parallel.

Optionally, in the wearable device of one embodiment of the invention:

the plurality of switch units comprise a first single-pole double-throw switch and a second single-pole double-throw (also called as a single-pole double-throw) switch;

in a high-level mode, the first single-pole double-throw switch and the second single-pole double-throw switch are both in a first switch position, thereby connecting the anode of the first energy storage assembly to the cathode of the second energy storage assembly; and

in the low-level mode:

the first single pole double throw switch is in a second switch position thereby connecting the cathode of the first energy storage component to the cathode of the second energy storage component; and is

The second single pole double throw switch is in a second switch position thereby connecting the anode of the first energy storage assembly to the anode of the second energy storage assembly.

Optionally, in the wearable device of one embodiment of the invention:

the plurality of switch units comprise two single-pole single-throw switches;

in the high-level mode:

a first of the two single pole single throw switches is in the off position, an

A second of the two single pole, single throw switches is in an engaged energized position, thereby connecting the anode of the first energy storage assembly to the cathode of the second energy storage assembly; and

in the low-level mode:

a first of the two single pole, single throw switches is in an engaged energized position thereby connecting the cathode of the first energy storage assembly to the cathode of the second energy storage assembly, an

The second of the two single pole single throw switches is in the off position.

Optionally, in the wearable device of an embodiment of the present invention, the energy storage device further includes at least one charging unit switch configured to connect and disconnect the first energy storage component and the second energy storage component to and from the charging unit.

Optionally, in the wearable device of one embodiment of the invention, in the high-level modality:

the anode of the light source plate is connected to the anode of the first energy storage assembly; and is

The cathode of the light source board is connected to the cathode of the first energy storage assembly.

Optionally, in the wearable device of an embodiment of the present invention, the energy storage device further comprises at least one load switch, the at least one load switch comprising at least two or more poles, wherein, in the high-level mode:

when the at least one load switch is set to one or more first switch positions:

the anode of the light source plate is connected to the anode of the first energy storage assembly, an

The cathode of the light source plate is connected to the cathode of the first energy storage assembly; and when the at least one load switch is set to one or more second switch positions:

the anode of the light source plate is connected to the anode of the second energy storage assembly, an

The cathode of the light source board is connected to the cathode of the first energy storage assembly.

Optionally, in the wearable device according to an embodiment of the present invention, the wearable device further includes a control circuit configured to set a position of the at least one load switch according to a state parameter of at least one of the first energy storage component and the second energy storage component when in the high-level mode.

Optionally, in the wearable device of one embodiment of the invention:

in the high mode, the energy storage device is configured to receive a charging voltage of 220 volts or 800 volts or more over 240 volts.

Optionally, in the wearable device of one embodiment of the invention, in the charging configuration, the energy storage device is configured to provide a voltage of 48 volts or 36 volts or more to the wearable device or the light source board.

Optionally, the wearable device of an embodiment of the present invention further includes an energy storage control unit configured to select between a low-level modality and a high-level modality. The topological connections of some components in the wearable device are shown in fig. 5.

In these respective embodiments, the electrical connection between the energy storage device and the external power source is dynamically adjusted according to a) the voltage change of the external power source 1978 or b) the energy requirement of the sound source module and/or the light source module, so that a stable and high-dynamic feed channel is established between i) the external power source and ii) the sound source module and/or the light source module through the centered energy storage device P77, thereby enabling the sound source module and/or the light source module to be adjusted in power with high dynamic and large variation amplitude as required.

For example, in some embodiments, a) the electrical connection relationship between the energy storage device and the light source board is dynamically switched between series and parallel through coordinated operation of a plurality of switch cells, or b) the electrical connection relationship between the energy storage device and the external power source is dynamically switched between series and parallel through coordinated operation of switch cells, which allows the feed path of "external power source → energy storage device", and/or the feed path of "energy storage device → sound source module and/or light source module" to be dynamically adapted to 1) the voltage variation of the external power source, or 2) the energy requirements of the sound source module and/or light source module.

As shown in fig. 3, the cerebral cortex of the user of the electronic device in some embodiments is divided into a plurality of regions X0001, X0002, X0003, X0004, X0005, X0006, X0007, and X0008, brain wave (EEG) intensities in the respective regions are respectively acquired by sensors distributed in a wearable device such as a helmet of the user, and the current center of gravity Y3001 of the whole of the brain waves of the cerebral cortex is calculated from the brain wave intensities of the plurality of regions X0001, X0002, X0003, X0004, X0005, X0006, X0007, and X0008; for example, if the EEG intensity for region X0001 is 1.2 and all other regions are 0, then the current center of gravity Y3001 is located at the geometric center of region X0001.

Further, a) the current first barycentric position is compared with b) the second barycentric position of the brain waves of the cerebral cortex (i.e. the average barycentric position of the brain waves in the cerebral cortex based on the sleep data of the healthy population), and the acousto-optic excitation is adjusted according to the difference between a) and b) so that the first barycentric position approaches to the second barycentric position, as shown in the figure, the barycentric position gradually changes from position Y3001 to position Y3002 through the adjustment of the digital experience, which is a process of gradually approaching to EEG barycentric position Y3003 of the cerebral cortex of the healthy human body. The second gravity center position Y3003 corresponds to the position of the gravity center of the cerebral cortex of the healthy human body in the process of interacting with the related digital experience and digital prescription. The method provides a visual expression mode for the change of the physiological indexes of the user, the physiological indexes of the user and the change tracks of the physiological indexes of the user adjusted along with the distribution of the acousto-optic experience can be checked by the electronic equipment held by the user along with the distribution of the digital experience and the digital prescription and applied to the user of the corresponding electronic equipment and the adjustment of the distribution content of the acousto-optic experience.

The step of "user's reaction/feedback tracked by electronic device" in some embodiments, further comprises the steps of:

(1) obtaining a sleep diary scale filled out by an insomniac

The sleep diary scale comprises a plurality of topic areas and corresponding answering areas, each topic area corresponds to the corresponding answering area, each answering area corresponds to one or more answering areas for insomniacs to fill, and the topic areas comprise two types, namely a basic information topic area for collecting user state information of the insomniacs and a special topic area for collecting sleep survey information designed for researching insomniacs.

Correspondingly optionally, the method of some embodiments further comprises the step of: (2) generating an insomnia management scheme aiming at an insomnia person according to the sleep knowledge and the sleep diary table of preset days:

the sleep knowledge includes cognitive behavior management (CBT-I) operation instructions and the like, wherein the CBT-I includes sleep hygiene education, stimulation control Therapy, sleep restriction Therapy and relaxation management. And generating an insomnia management scheme corresponding to the insomnia person according to the sleep knowledge and the sleep diary table of preset days.

Optionally, the method of some embodiments further comprises the step of: (3) after the insomnia person executes the generation of the insomnia management scheme, acquiring sleep parameters of the insomnia person through a sensor in the electronic device:

the sleep parameters include any one or more of heart rate data, temperature data, and exercise data. For example, heart rate data of the insomnia person is acquired by a heart rate sensor, temperature data of the insomnia person is acquired by a temperature sensor, and for example, the body surface temperature of the insomnia person is acquired by an infrared temperature sensor or other temperature sensors. The motion data of the insomnia people is acquired through the motion sensor and/or the pressure sensor so as to know whether the insomnia people have the actions of non-sleep motion or turning over and the like at present.

Furthermore, the heart rate sensor and the motion sensor can be arranged on the wearable device, and under the condition that the insomnia people sleep, various sleep parameters of the insomnia people can be measured through the wearable device. Of course, the sensor and the pressure sensor are also arranged at the intelligent mattress, and under the condition that the insomnia person is placed on the intelligent mattress, various sleep parameters of the insomnia person can be detected through the sensor arranged on the intelligent mattress.

Optionally, the method of some embodiments further comprises the step of: (4) adjusting and updating the insomnia management scheme according to the sleep parameters:

the insomnia management program is adjusted according to the monitored sleep parameters, and the time to go to bed, the time to get up, the time to use and the time to exercise in the insomnia management program can be periodically adjusted by referring to the above steps.

The invention guides or intervenes the sleep health of the user from the aspects of movement, sleep, diet and the like by combining the sleep parameters of the insomnia sufferer. And readjusting the insomnia management scheme of the user according to the monitored sleep parameters and by combining the execution condition of the insomnia sufferer so as to continuously optimize and improve the insomnia management scheme of the user. The adjusted insomnia management scheme is pushed to the insomnia sufferer, and the steps are repeatedly executed to continuously perform sleep intervention on the user, so that the sleep state of the user is continuously tracked and monitored step by step, the insomnia sufferer can gradually achieve enough sleep time, and the purpose of effectively improving the sleep quality of the insomnia sufferer is achieved.

In addition to the specific implementation methods described above, the method relies on a series of underlying software and hardware foundations.

In practice, the above-mentioned function distribution may be performed by different program modules according to requirements, that is, the internal structure of the device is divided into different program units or modules so as to perform all or part of the above-mentioned functions. Each program module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one processing unit, and the integrated unit may be implemented in a form of hardware, or may be implemented in a form of software program unit.

The wearable device can be a desktop computer, a notebook, a palm computer, a tablet computer, a mobile phone, a man-machine interaction screen and other devices. The wearable device may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that this is merely an example of a wearable device, and does not constitute a limitation of a wearable device, and may include more or fewer components than shown, or combine certain components, or different components, such as: the wearable device may also include input/output interfaces, display devices, network access devices, communication buses, communication interfaces, and the like. A communication interface and a communication bus, and may further comprise an input/output interface, wherein the processor, the memory, the input/output interface and the communication interface complete communication with each other through the communication bus. The memory stores a computer program, and the processor is used for executing the computer program stored on the memory to realize the sleep management system in the corresponding method embodiment.

The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory may be an internal storage unit of the wearable device, such as: a hard disk or memory of the wearable device. The memory may also be an external storage device of the wearable device, such as: the wearable device is provided with a plug-in hard disk, an intelligent memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) and the like. Further, the memory may also include both an internal storage unit of the wearable device and an external storage device. The memory is used to store the computer program and other programs and data required by the wearable device. The memory may also be used to temporarily store data that has been output or is to be output.

A communication bus is a circuit that connects the described elements and enables transmission between the elements. For example, the processor receives commands from other elements through the communication bus, decrypts the received commands, and performs calculations or data processing according to the decrypted commands. The memory may include program modules such as a kernel (kernel), middleware (middleware), an Application Programming Interface (API), and applications. The program modules may be comprised of software, firmware or hardware, or at least two of the same. The input/output interface forwards commands or data entered by a user via the input/output interface (e.g., sensor, keyboard, touch screen). The communication interface connects the wearable device with other network devices, user devices, networks. For example, the communication interface may be connected to a network by wire or wirelessly to connect to external other network devices or user devices. The wireless communication may include at least one of: wireless fidelity (WiFi), Bluetooth (BT), Near Field Communication (NFC), Global Positioning Satellite (GPS) and cellular communications, among others. The wired communication may include at least one of: universal Serial Bus (USB), high-definition multimedia interface (HDMI), asynchronous transfer standard interface (RS-232), and the like. The network may be a telecommunications network and a communications network. The communication network may be a computer network, the internet of things, a telephone network. The wearable device may connect to the network through a communication interface, and a protocol by which the wearable device communicates with other network devices may be supported by at least one of an application, an Application Programming Interface (API), middleware, a kernel, and a communication interface.

In an embodiment of the present invention, a storage medium stores at least one instruction, and the instruction is loaded and executed by a processor to implement the operations performed by the embodiments of the sleep management system. For example, the storage medium may be a read-only memory (ROM), a Random Access Memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

They may be implemented in program code that is executable by a computing device such that it is executed by the computing device, or separately, or as individual integrated circuit modules, or as a plurality or steps of individual integrated circuit modules.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.

The relative arrangement of parts and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the patent unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

Spatially relative terms, such as "above … …," "above … …," "above … …," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial relationship to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if a device in the figures is turned over, devices described as "above" or "on" other devices or configurations would then be oriented "below" or "under" the other devices or configurations. Thus, the exemplary term "above … …" can include both an orientation of "above … …" and "below … …". The device may be otherwise variously oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular is intended to include the plural unless the context clearly dictates otherwise, and it should be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of features, steps, operations, devices, components, and/or combinations thereof.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein.

The above is only a preferred embodiment of this patent and is not intended to limit the patent, and various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present patent shall be included in the protection scope of the present patent.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, so that various optional technical features can be combined with other embodiments in any reasonable manner, and the contents among the embodiments and under various headings can be combined in any reasonable manner. Each embodiment is described with emphasis on differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and "a plurality" typically includes at least two. It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

While specific embodiments of the present application have been described above, it will be understood by those skilled in the art that this is by way of illustration only, and that the scope of the present application is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the spirit and principles of this application, and these changes and modifications are intended to be included within the scope of this application.