阅读说明：本技术 一种植入式闭环系统中电信号识别处理方法和装置 (Electric signal identification processing method and device in implanted closed-loop system ) 是由 林婷 吴承瀚 陈新蕾 曹鹏 于 2021-02-05 设计创作，主要内容包括：本说明书实施例公开了一种植入式闭环系统中电信号识别处理方法和装置,包括：采集目标靶点位置处的生物电信号；基于第一类检测算法识别采集到的生物电信号是否满足触发刺激的约束条件；如果满足,则对目标靶点位置释放刺激信号,并记录与本次刺激相关的第一类信息；如果不满足,则基于第二类检测算法判断生物电信号是否异常；如果异常,则记录与异常的生物电信号相关的第二类信息。这样,在发作期间进行提前刺激干预,抑制病情发作；在病情发作间期进行记录,作为预后参考,可以有效利用发作间期的异常生物电信号的记录信息,对病情进行预测或对刺激诊疗方案进行调整,有效降低闭环系统的刺激次数,延长设备使用寿命,提升优化诊疗效果。(The embodiment of the specification discloses an electric signal identification processing method and device in an implanted closed-loop system, which comprises the following steps: collecting bioelectrical signals at the position of a target point of interest; identifying whether the acquired bioelectrical signals meet constraint conditions for triggering stimulation based on a first type of detection algorithm; if yes, releasing a stimulation signal to the target point position of the target, and recording first-class information related to the stimulation; if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm; if abnormal, record the second kind of information correlated to abnormal bioelectric signal. Thus, the early stimulation intervention is carried out during the attack, and the attack of the disease is inhibited; the method can be used for recording the disease state and the attack interval as prognosis reference, effectively utilizing the recorded information of abnormal bioelectric signals of the attack interval to predict the disease state or adjust a stimulation diagnosis and treatment scheme, effectively reducing the stimulation times of a closed-loop system, prolonging the service life of equipment and improving the optimized diagnosis and treatment effect.)

1. An electric signal identification processing method in an implanted closed-loop system is applied to the implanted closed-loop system, and the method comprises the following steps:

collecting bioelectrical signals at the position of a target point of interest;

identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm;

if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation;

if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm;

if abnormal, record the second kind of information correlated to abnormal bioelectric signal.

2. The method of claim 1, wherein the method further comprises:

adjusting the detection parameters and/or the generated stimulation pattern set in the first type of detection algorithm based on the recorded second type of information related to the abnormal bioelectric signal.

3. The method of claim 1, wherein the method further comprises:

determining an intervention prediction strategy based on the recorded first type information and second type information;

detecting and analyzing the bioelectrical signals at the newly acquired target point position of the target point based on the intervention prediction strategy;

if the detected bioelectric signal is determined to meet the intervention prediction strategy, performing intervention stimulation in advance, and recording first-class information related to the stimulation;

only the second type of information relating to the abnormal bioelectric signal is recorded if it is determined that the detected bioelectric signal does not satisfy the intervention prediction strategy.

4. A method for identification processing of electrical signals in an implantable closed loop system according to any of claims 1 to 3, wherein the first type of information comprises at least:

the contact, amplitude, frequency, pulse width and duration used by the stimulation; and the waveform, frequency and duration of the abnormal bioelectric signal intervened by the stimulation;

the second type of information includes: the waveform, frequency, duration of the bioelectric signal that is abnormal but does not trigger intervention, and the time information for analyzing rhythmicity.

5. A method for processing electrical signal identification in an implantable closed loop system according to any one of claims 1 to 3, wherein the first detection algorithm at least comprises: a line length algorithm, an area algorithm and a half-wave algorithm;

the second type of detection algorithm at least comprises: and (4) half-wave algorithm.

6. An apparatus for recognizing and processing electrical signals in an implanted closed-loop system, the apparatus being applied to the implanted closed-loop system and comprising:

the acquisition module is used for acquiring the bioelectrical signal at the position of the target point of interest;

the identification module is used for identifying whether the acquired bioelectrical signals meet the constraint condition of triggering stimulation or not based on a first-class detection algorithm;

the stimulation module is used for releasing a stimulation signal to the target point position if the stimulation is met, and recording first type information related to the stimulation;

the judging module is used for judging whether the bioelectrical signal is abnormal or not based on a second detection algorithm if the bioelectrical signal is not abnormal;

and a recording module for recording a second type of information related to the abnormal bioelectric signal if abnormal.

7. The apparatus for identification and processing of electrical signals in an implantable closed loop system of claim 6, further comprising:

and the adjusting module is used for adjusting the detection parameters and/or the generated stimulation mode set in the first detection algorithm based on the recorded second information related to the abnormal bioelectrical signals.

8. The apparatus for identification and processing of electrical signals in an implantable closed loop system of claim 6, further comprising:

the determining module is used for determining an intervention prediction strategy based on the recorded first type information and second type information;

the detection module is used for detecting and analyzing the bioelectrical signals at the newly acquired target point positions of the targets based on the intervention prediction strategy;

the stimulation module is further used for carrying out intervention stimulation in advance and recording first-class information related to the stimulation if the bioelectrical signal detected by the detection module is determined to meet the intervention prediction strategy;

the recording module is further configured to record only a second type of information associated with the abnormal bioelectric signal if it is determined that the detected bioelectric signal does not satisfy the intervention prediction policy.

9. The apparatus for recognizing and processing electrical signals in an implantable closed-loop system as claimed in any one of claims 6-8, wherein said first type of information comprises at least:

the stimulation contact, amplitude, frequency, pulse width and duration used by the stimulation; and the waveform, frequency and duration of the abnormal bioelectric signal intervened by the stimulation;

the second type of information includes: the waveform, frequency, duration of the bioelectric signal that is abnormal but does not trigger intervention, and time information for analyzing rhythmicity.

10. An implantable closed loop system, comprising an electrical signal identification processing device in the implantable closed loop system according to any one of claims 6 to 9.

Technical Field

The present invention relates to the technical field of medical devices, and in particular, to a method and an apparatus for identifying and processing an electrical signal in an implantable closed-loop system.

Background

At present, implantable medical devices are widely applied to medical clinic to help patients to diagnose and treat diseases. The implanted electric stimulation apparatus mainly comprises an implanted electric pulse generator implanted in a living body, a stimulation electrode and an external controller. The electric stimulation pulse generated by the implanted electric pulse generator is transmitted to the stimulation electrode, and the stimulation electrode electrically stimulates a specific nerve target point, so that diseases such as Parkinson, epilepsy and the like can be diagnosed and treated.

However, abnormal bioelectric signals which are insufficient to cause the onset of a disease are often not processed during the course of treatment. The abnormal bioelectric signal for triggering the intervention stimulation often causes over-stimulation due to intolerance of the patient and the like.

Disclosure of Invention

One or more embodiments of the present disclosure are to provide a method and an apparatus for identifying and processing an electrical signal in an implanted closed-loop system, so as to reduce the number of stimulation times implemented in the closed-loop system, prolong the service life of an implanted device, and optimize and improve the diagnosis and treatment effects.

To solve the above technical problem, one or more embodiments of the present specification are implemented as follows:

in a first aspect, a method for identifying and processing an electrical signal in an implantable closed-loop system is provided, and the method is applied to the implantable closed-loop system and includes:

collecting bioelectrical signals at the position of a target point of interest;

identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm;

if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation;

if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm;

if abnormal, record the second kind of information correlated to abnormal bioelectric signal.

In a second aspect, an apparatus for recognizing and processing an electrical signal in an implantable closed-loop system is provided, which is applied in the implantable closed-loop system, and the apparatus includes:

the acquisition module is used for acquiring the bioelectrical signal at the position of the target point of interest;

the identification module is used for identifying whether the acquired bioelectrical signals meet the constraint condition of triggering stimulation or not based on a first-class detection algorithm;

the stimulation module is used for releasing a stimulation signal to the target point position if the stimulation is met, and recording first type information related to the stimulation;

the judging module is used for judging whether the bioelectrical signal is abnormal or not based on a second detection algorithm if the bioelectrical signal is not abnormal;

and a recording module for recording a second type of information related to the abnormal bioelectric signal if abnormal.

In a third aspect, an implantable closed-loop system is provided, which includes an electrical signal identification processing device in the implantable closed-loop system.

As can be seen from the technical solutions provided in one or more embodiments of the present disclosure, a bioelectric signal at a target point of interest is collected; identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm; if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation; if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm; if abnormal, record the second kind of information correlated to abnormal bioelectric signal. The embodiment of the specification not only records abnormal bioelectric signals during the attack, but also classifies and records abnormal bioelectric signals which are insufficient to cause stimulation during the attack. Thus, the early stimulation intervention is carried out during the attack, and the attack of the disease is inhibited; the method can be used for recording the disease attack interval as a prognosis reference of a specific therapy, effectively utilizing the recorded information of the abnormal bioelectric signals of the disease attack interval to predict the disease attack or adjust a stimulation diagnosis and treatment scheme, effectively reducing the stimulation times of a closed-loop system, prolonging the service life of implantable equipment and improving the optimized diagnosis and treatment effect.

Drawings

In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, reference will now be made briefly to the attached drawings, which are needed in the description of one or more embodiments or prior art, and it should be apparent that the drawings in the description below are only some of the embodiments described in the specification, and that other drawings may be obtained by those skilled in the art without inventive exercise.

Fig. 1 is a schematic diagram illustrating a step of a method for identifying and processing an electrical signal in an implantable closed-loop system according to an embodiment of the present disclosure.

Fig. 2 is a second schematic step diagram of a method for identifying and processing an electrical signal in an implantable closed-loop system according to an embodiment of the present disclosure.

Fig. 3 is a third step schematic diagram of a method for identifying and processing an electrical signal in an implantable closed-loop system according to an embodiment of the present disclosure.

Fig. 4 is a schematic structural diagram of an electrical signal identification processing apparatus in an implantable closed-loop system according to an embodiment of the present disclosure.

Fig. 5 is a second schematic structural diagram of an electrical signal identification processing apparatus in an implantable closed-loop system according to an embodiment of the present disclosure.

Fig. 6 is a third schematic structural diagram of an electrical signal recognition processing apparatus in an implantable closed-loop system according to an embodiment of the present disclosure.

Fig. 7 is a schematic structural diagram of an electronic device provided in an embodiment of the present specification.

Detailed Description

In order to make the technical solutions in the present specification better understood, the technical solutions in one or more embodiments of the present specification will be clearly and completely described below with reference to the accompanying drawings in one or more embodiments of the present specification, and it is obvious that the one or more embodiments described are only a part of the embodiments of the present specification, and not all embodiments. All other embodiments that can be derived by a person skilled in the art from one or more of the embodiments described herein without making any inventive step shall fall within the scope of protection of this document.

Example one

Referring to fig. 1, a schematic step diagram of a method for identifying and processing an electrical signal in an implantable closed-loop system provided in an embodiment of the present disclosure, where the electrical signal may specifically be a bioelectrical signal, and the bioelectrical signal processing scheme is applied in the implantable closed-loop system, and the method may include the following steps:

step 102: and collecting the bioelectrical signal at the target point position of interest.

Specifically, bioelectrical signals are collected by using electrodes implanted at the target site of interest and buffered to the MCU.

Step 104: identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm; if so, step 106 is performed, otherwise, step 108 is performed.

The first class of detection algorithms may include: detection algorithms such as a line length algorithm, an area algorithm, a half-wave algorithm and the like; if a seizure is detected, for example, an epileptic seizure, then it is determined that the constraints that trigger the stimulation are satisfied. Therefore, the constraint condition of triggering stimulation is the condition that the first detection algorithm detects the disease attack. Specifically, the frequency may be abnormal, or the amplitude may suddenly rise above a threshold value. And parameter reference can be flexibly set according to detection requirements.

Step 106: and releasing a stimulation signal to the target point position of the target, and recording first type information related to the stimulation.

When the first type of detection algorithm is used for identifying that the current bioelectric signal meets the condition of triggering stimulation, the stimulation signal is released to the target point position, namely stimulation treatment is carried out, and the disease attack is stopped. And recording the first type of information related to the stimulation, wherein the specific recording process can be that the bioelectrical signal buffered by the MCU is transmitted to the FRAM. Wherein the first type of information at least comprises: the contact, amplitude, frequency, pulse width, duration and the like used by the stimulation; and the waveform, frequency, duration, etc. of the abnormal bioelectric signal intervened by the present stimulation.

Step 108: judging whether the bioelectrical signal is abnormal or not based on a second detection algorithm; if so, go to step 110, otherwise, do not.

The second detection algorithm is used for detecting low-frequency (1-10 Hz) spike-slow compound waves, spike-slow compound waves and the like which are different from a background interval aiming at abnormal bioelectricity signals in an inter-attack interval, and the implementation mode comprises a half-wave algorithm and the like. It should be understood that the detection decision in step 108 is the detection process for abnormal bioelectric signals that are insufficient to trigger stimulation, i.e., such abnormal signals need to be detected. Wherein, the inter-attack period refers to the period of no attack.

Step 110: a second type of information relating to the abnormal bioelectric signal is recorded.

The second type of information includes: the waveform, frequency, duration of the bioelectric signal that is abnormal but does not trigger intervention, and time information for analyzing rhythmicity, and the like. The recording process is similar to the first type of information.

It can be seen that the embodiments of the present specification not only record abnormal bioelectric signals during an episode, but also classify and record abnormal bioelectric signals in which an episode interval is insufficient to cause stimulation. Therefore, the recording information of the abnormal bioelectricity signals at the interval of attack can be effectively utilized to predict the disease attack or adjust the stimulation diagnosis and treatment scheme, so that the stimulation times of a closed-loop system are effectively reduced, the service life of implantable equipment is prolonged, and the optimized diagnosis and treatment effect is improved.

Further, referring to fig. 2, the method further includes:

step 112: adjusting the detection parameters and/or the generated stimulation pattern set in the first type of detection algorithm based on the recorded second type of information related to the abnormal bioelectric signal.

Therefore, when the second type of information is not obviously reduced, the first type of detection algorithm is indicated to have poor prognosis, and a doctor is prompted to adjust the detection parameters or the stimulation scheme of the first type of detection algorithm.

An implementation solution, shown with reference to fig. 3, the method further comprises:

step 114: and determining an intervention prediction strategy based on the recorded first type information and second type information.

Specifically, the disease onset rules can be summarized according to the bioelectric signals during or during the disease onset, such as whether the disease onset will occur during sleep, whether abnormal brain electrical signals will be generated during sleep but the disease onset is insufficient. These can be used as a strategy to predict the condition, with subsequent decisions on whether to intervene prematurely or to merely record that no intervention is taking place.

Step 116: detecting and analyzing the bioelectrical signals at the newly acquired target point position of the target point based on the intervention prediction strategy;

step 118: if the detected bioelectric signal is determined to meet the intervention prediction strategy, performing intervention stimulation in advance, and recording first-class information related to the stimulation;

step 120: only the second type of information relating to the abnormal bioelectric signal is recorded if it is determined that the detected bioelectric signal does not satisfy the intervention prediction strategy.

It should be understood that the bioelectrical signals referred to in the embodiments of the present specification may include at least: EEG signal, deep electrophysiological signal of brain, bioelectric signal of cerebral cortex, or central nerve signal.

The embodiment of the specification collects a bioelectrical signal at a target point position of interest; identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm; if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation; if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm; if abnormal, record the second kind of information correlated to abnormal bioelectric signal. The embodiment of the specification not only records abnormal bioelectric signals during the attack, but also classifies and records abnormal bioelectric signals which are insufficient to cause stimulation during the attack. Thus, the early stimulation intervention is carried out during the attack, and the attack of the disease is inhibited; the method can be used for recording the disease attack interval as a prognosis reference of a specific therapy, effectively utilizing the recorded information of the abnormal bioelectric signals of the disease attack interval to predict the disease attack or adjust a stimulation diagnosis and treatment scheme, effectively reducing the stimulation times of a closed-loop system, prolonging the service life of implantable equipment and improving the optimized diagnosis and treatment effect.

Example two

Referring to fig. 4, an electrical signal identification processing apparatus in an implantable closed-loop system is provided for the embodiment of the present specification, and is applied to the implantable closed-loop system, where the apparatus includes:

an acquisition module 402 for acquiring a bioelectrical signal at a target point location of interest;

an identifying module 404, configured to identify whether the acquired bioelectric signal meets a constraint condition of triggering stimulation based on a first class detection algorithm;

a stimulation module 406, configured to release a stimulation signal to the target point location if the first type of information is satisfied, and record first type of information related to the current stimulation;

a judging module 408, configured to, if not, judge whether the bioelectric signal is abnormal based on a second detection algorithm;

a recording module 410 for recording a second type of information related to the abnormal bioelectric signal if abnormal.

Optionally, as an embodiment, referring to fig. 5, the apparatus further includes:

an adjusting module 412, configured to adjust the detection parameters and/or the generated stimulation pattern set in the first type of detection algorithm based on the recorded second type of information related to the abnormal bioelectric signal.

In a specific implementation manner of the embodiment of the present specification, referring to fig. 6, the apparatus further includes:

a determining module 414, configured to determine an intervention prediction policy based on the recorded first type information and second type information;

a detection module 416, configured to perform detection analysis on the bio-electrical signal at the newly acquired target point of interest based on the intervention prediction strategy;

the stimulation module 406 is further configured to perform intervention stimulation in advance and record first type information related to the current stimulation if it is determined that the bioelectrical signal detected by the detection module satisfies the intervention prediction policy;

the recording module 410 is further configured to record only the second type of information associated with the abnormal bioelectric signal if it is determined that the detected bioelectric signal does not satisfy the intervention prediction policy.

In a specific implementation manner of the embodiment of this specification, the first type of information at least includes:

the contact, amplitude, frequency, pulse width, duration and the like used by the stimulation; and the waveform, frequency, duration, etc. of the abnormal bioelectric signal intervened by the stimulation;

the second type of information includes: the waveform, frequency, duration of the bioelectric signal that is abnormal but does not trigger intervention, and the time information for analyzing rhythmicity.

The embodiment of the specification collects a bioelectrical signal at a target point position of interest; identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm; if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation; if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm; if abnormal, record the second kind of information correlated to abnormal bioelectric signal. The embodiment of the specification not only records abnormal bioelectric signals during the attack, but also classifies and records abnormal bioelectric signals which are insufficient to cause stimulation during the attack. Thus, the early stimulation intervention is carried out during the attack, and the attack of the disease is inhibited; the method can be used for recording the disease attack interval as a prognosis reference of a specific therapy, effectively utilizing the recorded information of the abnormal bioelectric signals of the disease attack interval to predict the disease attack or adjust a stimulation diagnosis and treatment scheme, effectively reducing the stimulation times of a closed-loop system, prolonging the service life of implantable equipment and improving the optimized diagnosis and treatment effect.

EXAMPLE III

The embodiment of the specification also provides an implanted closed-loop system which comprises an electric signal identification processing device in the implanted closed-loop system. In addition, the device also comprises extracorporeal equipment and other existing functional modules.

The functions and effects of the implanted system can be realized with reference to the first embodiment, which is not described herein.

It can be seen that the embodiments of the present specification not only record abnormal bioelectric signals during an episode, but also classify and record abnormal bioelectric signals in which an episode interval is insufficient to cause stimulation. Therefore, the recording information of the abnormal bioelectricity signals at the interval of attack can be effectively utilized to predict the disease attack or adjust the stimulation diagnosis and treatment scheme, so that the stimulation times of a closed-loop system are effectively reduced, the service life of implantable equipment is prolonged, and the optimized diagnosis and treatment effect is improved.

Example four

Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present specification. Referring to fig. 7, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.

The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 7, but this does not indicate only one bus or one type of bus.

And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.

The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the bioelectrical signal processing device on a logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:

collecting bioelectrical signals at the position of a target point of interest;

identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm;

if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation;

if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm;

if abnormal, record the second kind of information correlated to abnormal bioelectric signal.

The method performed by the apparatus disclosed in the embodiments of fig. 1-3 of the present specification can be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The methods, steps, and logic blocks disclosed in one or more embodiments of the present specification may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with one or more embodiments of the present disclosure may be embodied directly in hardware, in a software module executed by a hardware decoding processor, or in a combination of the hardware and software modules executed by a hardware decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

The electronic device may also execute the method shown in fig. 1-3 and implement the functions of the corresponding apparatus in the embodiments shown in fig. 1-3, which are not described herein again in this specification.

Of course, besides the software implementation, the electronic device of the embodiment of the present disclosure does not exclude other implementations, such as a logic device or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or a logic device.

The embodiment of the specification collects a bioelectrical signal at a target point position of interest; identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm; if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation; if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm; if abnormal, record the second kind of information correlated to abnormal bioelectric signal. The embodiment of the specification not only records abnormal bioelectric signals during the attack, but also classifies and records abnormal bioelectric signals which are insufficient to cause stimulation during the attack. Thus, the early stimulation intervention is carried out during the attack, and the attack of the disease is inhibited; the method can be used for recording the disease attack interval as a prognosis reference of a specific therapy, effectively utilizing the recorded information of the abnormal bioelectric signals of the disease attack interval to predict the disease attack or adjust a stimulation diagnosis and treatment scheme, effectively reducing the stimulation times of a closed-loop system, prolonging the service life of implantable equipment and improving the optimized diagnosis and treatment effect.

Example four

Embodiments of the present specification also provide a computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a portable electronic device comprising a plurality of application programs, enable the portable electronic device to perform the method of the embodiments shown in fig. 1-3, and in particular to perform the method of:

collecting bioelectrical signals at the position of a target point of interest;

identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm;

if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation;

if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm;

if abnormal, record the second kind of information correlated to abnormal bioelectric signal.

The embodiment of the specification collects a bioelectrical signal at a target point position of interest; identifying whether the acquired bioelectrical signal meets a constraint condition for triggering stimulation based on a first type of detection algorithm; if yes, releasing a stimulation signal to the target point position, and recording first type information related to the stimulation; if not, judging whether the bioelectric signal is abnormal based on a second detection algorithm; if abnormal, record the second kind of information correlated to abnormal bioelectric signal. The embodiment of the specification not only records abnormal bioelectric signals during the attack, but also classifies and records abnormal bioelectric signals which are insufficient to cause stimulation during the attack. Thus, the early stimulation intervention is carried out during the attack, and the attack of the disease is inhibited; the method can be used for recording the disease attack interval as a prognosis reference of a specific therapy, effectively utilizing the recorded information of the abnormal bioelectric signals of the disease attack interval to predict the disease attack or adjust a stimulation diagnosis and treatment scheme, effectively reducing the stimulation times of a closed-loop system, prolonging the service life of implantable equipment and improving the optimized diagnosis and treatment effect.

In short, the above description is only a preferred embodiment of the present disclosure, and is not intended to limit the scope of the present disclosure. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present specification shall be included in the protection scope of the present specification.

The system, apparatus, module or unit illustrated in one or more of the above embodiments may be implemented by a computer chip or an entity, or by an article of manufacture with a certain functionality. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

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, and each embodiment focuses on the 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 foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.