阅读说明：本技术 一种呼吸异常智能侦测系统 (Intelligent respiratory anomaly detection system ) 是由 王苹 于 2021-07-21 设计创作，主要内容包括：本发明公开一种呼吸异常智能侦测系统,所述侦测系统包括：活动臂、追踪模块、探测模块以及控制模块；所述活动臂包括固定于床上的主梁以及位于活动臂最远端的移动端；所述追踪模块安装于使用者头部斜上方,使用传感器追踪使用者的脸部目标位置进行位置坐标识别,并将识别到的位置坐标上传到所述控制模块；所述探测模块安装于所述活动臂的移动端,伴随所述移动端移动到目标位置进行呼吸气体的检测；所述控制模块通过电路连接所述活动臂、所述追踪模块及所述探测模块；所述控制模块根据所述追踪模块识别到的位置坐标,发送驱动指令移动所述活动臂,将所述探测模块放置到使用者鼻部前的适当位置后开启呼吸监测。(The invention discloses an intelligent detection system for respiratory abnormality, which comprises: the device comprises a movable arm, a tracking module, a detection module and a control module; the movable arm comprises a main beam fixed on the bed and a movable end positioned at the farthest end of the movable arm; the tracking module is arranged above the head of a user in an inclined manner, a sensor is used for tracking the target position of the face of the user to identify the position coordinates, and the identified position coordinates are uploaded to the control module; the detection module is arranged at the moving end of the movable arm and detects the breathing gas along with the movement of the moving end to a target position; the control module is connected with the movable arm, the tracking module and the detection module through a circuit; and the control module sends a driving instruction to move the movable arm according to the position coordinate identified by the tracking module, and the detection module is placed at a proper position in front of the nose of the user to start respiration monitoring.)

1. An intelligent breathing abnormality detection system, comprising: the device comprises a movable arm, a tracking module, a detection module and a control module; the movable arm comprises a main beam fixed on the bed and a movable end positioned at the farthest end of the movable arm; the tracking module is arranged above the head of a user in an inclined manner, the position coordinate recognition is carried out by tracking the target position of the face of the user by using the sensor, and the recognized position coordinate is uploaded to the control module; the detection module is arranged at the moving end of the movable arm and detects the breathing gas along with the movement of the moving end to a target position; the control module is in communication connection with the movable arm, the tracking module and the detection module; the control module sends a driving instruction to move the movable arm according to the position coordinate identified by the tracking module, and starts respiration monitoring after the detection module is placed at a proper position in front of the nose of a user;

the tracking module adopts a photoelectric night vision sensor as a main vision acquisition element; the detection system firstly adopts the tracking module to scan and collect face images of the face of the user; the photoelectric night vision sensor detects the characteristic quantity of each part of the face of a user in a grid dividing mode, digitalizes the characteristic quantity of the face information of the user, stores the digitalized characteristic quantity in the control module and focuses on the nose area of the user; when the position and the posture of the face of the user change during sleeping, the control module determines the nose position coordinate of the user and drives the moving end to move towards the nose position coordinate.

2. The system of claim 1, wherein the movable arm comprises a plurality of sub-movable arms; one end of each of the two sub movable arms is connected through a movable joint, so that the two sub movable arms rotate around the movable joint at one end of each sub movable arm in at least one degree of freedom; at least one section of the sub-movable arm is provided with a group of link mechanisms and a driver, and the sub-movable arm is driven to rotate around the movable joint at one end of the sub-movable arm.

3. The system of claim 2, wherein the driver comprises at least one of: pneumatic cylinder, electric jar, electronic slide rail, motor element.

4. The system as claimed in claim 3, wherein the electro-optical night vision sensor is used for collecting the face information of the user in a low light environment; the tracking module comprises a visual computing system; the vision operation system can process the facial optical information acquired by the photoelectric night vision sensor into digital information, and converts the digital information into coordinate information which can be digitally described through conversion.

5. The system of claim 4, wherein the coordinate information of the visual computing system includes coordinate information of the target object in the imaging plane and depth information of the target object in the visual depth.

6. The system of claim 5, wherein the detection module comprises an acoustic sensor; the sound sensor collects sound information in the breathing process of a user, converts the sound information into digital information and uploads the digital information to the control module; the sound information collected by the sound sensor comprises sound volume, sound production frequency and sound noise.

7. The system of claim 6, wherein the detection module comprises a gas composition analyzer; the gas component analyzer collects and analyzes the exhaled gas of a user; the gas component analyzer is used for analyzing the component content of at least one of the following substances in gas: oxygen, nitrogen, carbon dioxide, carbon oxides, oxygen-containing organic compounds.

8. The system of claim 7, comprising the following target tracking algorithm:

s1: the tracking module acquires the coordinate position (x, y, z) of the nose of a user, wherein x and y are plane position coordinates, and z is a depth position coordinate;

s2: judging an included angle theta between the face orientation of the user and the vertical direction;

s3: driving the movable arm to move, and moving the moving end to (x, y, z + h), wherein h is a monitoring distance, and an included angle between the moving end and the vertical direction is theta;

s4: starting the detection module to perform pre-acquisition, and determining whether the numerical value of the acquired information reaches the threshold value of the lowest analysis amount;

s5: if the threshold value of the minimum analysis amount is reached, entering conventional collection; if the threshold value of the minimum analysis amount is not reached, the target position is confirmed again, and the algorithm steps from S1 to S4 are repeated.

9. The system of claim 8, wherein the system comprises an electronic device; the electronic device includes: a processor, a memory, and a bus; the memory stores machine-readable instructions executable by the processor, the processor and the memory communicating over a bus when the electronic device is operating; the memory comprises a control method and a data processing program of the respiration adjusting device in the sleep state; the method for controlling the breathing adjustment device in sleep state and the data processing program when executed by the processor implement the algorithm steps as claimed in claim 8, which are applicable to an intelligent breathing abnormality detection system.

Technical Field

The invention relates to the technical field of breath detection. In particular to an intelligent respiratory anomaly detection system.

Background

Respiration is a basic physiological function of human beings, is a way for exchanging gas between the human body and the outside, and is closely related to the health of human bodies. Every breath of a human includes biomarkers reflecting the physiological/pathological state of various organs of the body, and the markers generated by the metabolism of the organs of various parts of the body reach the alveoli along with the blood circulation and are discharged out of the body through expiration. The exhaled gas not only contains widely known components of oxygen, nitrogen, carbon dioxide and water vapor, but also contains up to 100-200 trace volatile organic compounds which are present and reflect physiological states of various organs of the body. At present, a great deal of clinical researches show that the exhalation process in respiration is an important part of metabonomics and is terminal presentation in the metabolic process of various diseases, and an exhalation process analysis instrument is used for analyzing volatile metabolites in exhalation, so that accurate diagnosis, early warning, curative effect and disease progress tracking of various diseases such as infectious diseases, chronic diseases, cancers and the like can be realized. Therefore, by detecting the change of the quality and quantity of the volatile organic compounds, the pathophysiology condition of the organism can be known.

Furthermore, in daily activities, the breathing state of the human body is in an active state, the content of the exhaled gas is large in floating, and in sleeping, the human body is in a relatively stable resting state, so that the measurement of the component data of the exhaled gas in sleeping can accurately indicate the current physical condition.

Referring to the related published technical solutions, US2021187230(a1) proposes a gas analysis mask for detecting daily respiratory gases, CN111012306(a) proposes an intelligent algorithm for analyzing respiratory states by using an intelligent network, WO2020109915(a1) proposes an analyzer for forming visualizations by collecting and analyzing respiratory parameters, and the like. The above disclosed techniques mostly require the deployment of large detection devices, which however do not provide sufficient detection comfort, especially for the comfort of the user during sleep.

Disclosure of Invention

The invention aims to provide an intelligent breathing abnormality detection system, which comprises a detector for intelligently tracking the face, particularly the nasal cavity and the mouth, and a set of analysis equipment, and can periodically detect the breathing state of a user during the sleep of the user and reduce the interference of the detection system to the user during the detection process as much as possible.

The invention adopts the following technical scheme:

an intelligent breathing abnormality detection system, comprising: the device comprises a movable arm, a tracking module, a detection module and a control module; the movable arm comprises a main beam fixed on the bed and a movable end positioned at the farthest end of the movable arm; the tracking module is arranged above the head of a user in an inclined manner, the position coordinate recognition is carried out by tracking the target position of the face of the user by using the sensor, and the recognized position coordinate is uploaded to the control module; the detection module is arranged at the moving end of the movable arm and detects the breathing gas along with the movement of the moving end to a target position; the control module is in communication connection with the movable arm, the tracking module and the detection module; the control module sends a driving instruction to move the movable arm according to the position coordinate identified by the tracking module, and starts respiration monitoring after the detection module is placed at a proper position in front of the nose of a user;

the tracking module adopts a photoelectric night vision sensor as a main vision acquisition element; the detection system firstly adopts the tracking module to scan and collect face images of the face of the user; the photoelectric night vision sensor detects the characteristic quantity of each part of the face of a user in a grid dividing mode, digitalizes the characteristic quantity of the face information of the user, stores the digitalized characteristic quantity in the control module and focuses on the nose area of the user; when the position and the posture of the face of a user change during sleeping, the control module determines the position coordinates of the nose of the user and drives the moving end to move towards the position coordinates of the nose;

the movable arm comprises a plurality of sub-movable arms; one end of each of the two sub movable arms is connected through a movable joint, so that the two sub movable arms rotate around the movable joint at one end of each sub movable arm in at least one degree of freedom; at least one section of the sub-movable arm is provided with a group of link mechanisms and a driver, and the sub-movable arm is driven to rotate around the movable joint at one end of the sub-movable arm;

the driver includes at least one of: the device comprises a hydraulic cylinder, an electric slide rail and a motor assembly;

the photoelectric night vision sensor is used for collecting the face information of a user in a low-light environment; the tracking module comprises a visual computing system; the vision operation system can process the facial optical information acquired by the photoelectric night vision sensor into digital information, and converts the digital information into coordinate information which can be digitally described through conversion;

the coordinate information of the visual operation system comprises coordinate information of a target object on an imaging plane and depth information of the target object on a visual depth;

the detection module comprises a sound sensor; the sound sensor collects sound information in the breathing process of a user, converts the sound information into digital information and uploads the digital information to the control module; the sound information collected by the sound sensor comprises sound volume, sound frequency and sound noise;

the detection module comprises a gas composition analyzer; the gas component analyzer collects and analyzes the exhaled gas of a user; the gas component analyzer is used for analyzing the component content of at least one of the following substances in gas: oxygen, nitrogen, carbon dioxide, carbon oxides, oxygen-containing organic compounds;

the system for intelligently detecting the respiratory abnormality comprises the following target object tracking algorithm:

s1: the tracking module acquires the coordinate position (x, y, z) of the nose of a user, wherein x and y are plane position coordinates, and z is a depth position coordinate;

s2: judging an included angle theta between the face orientation of the user and the vertical direction;

s3: driving the movable arm to move, and moving the moving end to (x, y, z + h), wherein h is a monitoring distance, and an included angle between the moving end and the vertical direction is theta;

s4: starting the detection module to perform pre-acquisition, and determining whether the numerical value of the acquired information reaches the threshold value of the lowest analysis amount;

s5: if the threshold value of the minimum analysis amount is reached, entering conventional collection; if the minimum analysis amount threshold value is not reached, confirming the target position again, and repeating the algorithm steps from S1 to S4;

the beneficial effects obtained by the invention are as follows:

1. the intelligent detection system adopts the multi-degree-of-freedom movable arm to cover the displacement and depth positions in the range, so as to realize flexible and variable body position detection;

2. the intelligent detection system does not need a user to wear any mask or detection device, and is suitable for the user to carry out non-inductive detection in sleep;

3. the analysis scheme adopted by the intelligent detection system can achieve the detection of trace elements of exhaled gas from the most basic respiratory parameters, and different detection functions can be realized only by upgrading the analysis module, so that the intelligent detection system can adapt to different production costs and specific detection requirements of users;

4. the storage device adopts modularized programmable equipment and parts, and is convenient for system maintenance and technical upgrade in the future.

Drawings

The invention will be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate corresponding parts throughout the different views.

FIG. 1 is a schematic view of a use arrangement of the present invention;

FIG. 2 is a schematic view of the movable arm structure according to the present invention;

FIG. 3 is a schematic view of the moving wheel of the present invention;

FIG. 4 is a schematic view of the movement pattern of the slider according to the present invention;

fig. 5 is a schematic diagram of the tracking module identifying the nose region after performing image gridding on a face;

FIG. 6 is a schematic diagram of a characteristic curve drawn by collecting respiratory characteristic parameters;

the reference numbers illustrate: 10-a movable arm; 20-a detection module; 30-a tracking module; 101-a first sub-movable arm; 102-a second sub-movable arm; 103-a third sub-movable arm; 104-a fourth sub-movable arm; 110-main beam; 111-a movable bolt; 112-a movable bolt; 113-a movable bolt; 114-a fixed seat; 115-electric slide rail; 116-a first telescopic electric cylinder; 117-second telescopic electric cylinder; 118-a hoop; 119-a slide; 301-a hub; 302-a roller; 105 a-a left first moving wheel; 105 b-a right first moving wheel; 105 c-a left second moving wheel; 105 d-right second moving wheel.

Detailed Description

In order to make the technical solution and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the embodiments thereof; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. Other systems, methods, and/or features of the present embodiments will become apparent to those skilled in the art upon review of the following detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the invention, and be protected by the accompanying claims. Additional features of the disclosed embodiments are described in, and will be apparent from, the detailed description that follows.

The same or similar reference numerals in the drawings of the embodiments of the present invention correspond to the same or similar components; in the description of the present invention, it is to be understood that if there is an orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", etc. based on the orientation or positional relationship shown in the drawings, it is only for convenience of description and simplification of description, but it is not intended to indicate or imply that the device or assembly referred to must have a specific orientation.

The first embodiment is as follows:

as shown in fig. 1, an intelligent breathing abnormality detection system is characterized in that the detection system comprises: the device comprises a movable arm, a tracking module, a detection module and a control module; the movable arm comprises a main beam fixed on the bed and a movable end positioned at the farthest end of the movable arm; the tracking module is arranged above the head of a user in an inclined manner, the position coordinate recognition is carried out by tracking the target position of the face of the user by using the sensor, and the recognized position coordinate is uploaded to the control module; the detection module is arranged at the moving end of the movable arm and detects the breathing gas along with the movement of the moving end to a target position; the control module is in communication connection with the movable arm, the tracking module and the detection module; the control module sends a driving instruction to move the movable arm according to the position coordinate identified by the tracking module, and starts respiration monitoring after the detection module is placed at a proper position in front of the nose of a user;

the tracking module adopts a photoelectric night vision sensor as a main vision acquisition element; the detection system firstly adopts the tracking module to scan and collect face images of the face of the user; the photoelectric night vision sensor detects the characteristic quantity of each part of the face of a user in a grid dividing mode, digitalizes the characteristic quantity of the face information of the user, stores the digitalized characteristic quantity in the control module and focuses on the nose area of the user; when the position and the posture of the face of a user change during sleeping, the control module determines the position coordinates of the nose of the user and drives the moving end to move towards the position coordinates of the nose;

the movable arm comprises a plurality of sub-movable arms; one end of each of the two sub movable arms is connected through a movable joint, so that the two sub movable arms rotate around the movable joint at one end of each sub movable arm in at least one degree of freedom; at least one section of the sub-movable arm is provided with a group of link mechanisms and a driver, and the sub-movable arm is driven to rotate around the movable joint at one end of the sub-movable arm;

the driver includes at least one of: the device comprises a hydraulic cylinder, an electric slide rail and a motor assembly;

the photoelectric night vision sensor is used for collecting the face information of a user in a low-light environment; the tracking module comprises a visual computing system; the vision operation system can process the facial optical information acquired by the photoelectric night vision sensor into digital information, and converts the digital information into coordinate information which can be digitally described through conversion;

the coordinate information of the visual operation system comprises coordinate information of a target object on an imaging plane and depth information of the target object on a visual depth;

the detection module comprises a sound sensor; the sound sensor collects sound information in the breathing process of a user, converts the sound information into digital information and uploads the digital information to the control module; the sound information collected by the sound sensor comprises sound volume, sound frequency and sound noise;

the detection module comprises a gas composition analyzer; the gas component analyzer collects and analyzes the exhaled gas of a user; the gas component analyzer is used for analyzing the component content of at least one of the following substances in gas: oxygen, nitrogen, carbon dioxide, carbon oxides, oxygen-containing organic compounds;

the system for intelligently detecting the respiratory abnormality comprises the following target object tracking algorithm:

s1: the tracking module acquires the coordinate position (x, y, z) of the nose of a user, wherein x and y are plane position coordinates, and z is a depth position coordinate;

s2: judging an included angle theta between the face orientation of the user and the vertical direction;

s3: driving the movable arm to move, and moving the moving end to (x, y, z + h), wherein h is a monitoring distance, and an included angle between the moving end and the vertical direction is theta;

s4: starting the detection module to perform pre-acquisition, and determining whether the numerical value of the acquired information reaches the threshold value of the lowest analysis amount;

s5: if the threshold value of the minimum analysis amount is reached, entering conventional collection; if the minimum analysis amount threshold value is not reached, confirming the target position again, and repeating the algorithm steps from S1 to S4;

FIG. 2 shows a schematic diagram of one embodiment of the present invention; firstly, determining the position of a user who usually lies flat, and determining the position of the head of the user when lying flat; the main beam 110 of the movable arm 10 is fixed at the position obliquely above the head position by screws; the lowermost end of the main beam comprises a fixed seat 114; the bottom of the fixed seat comprises a group of sliding mechanisms, such as rollers or rolling wheels, so that the fixed seat can axially rotate around the main beam; the movable arm comprises a first sub-movable arm 101; the first end of the first sub-movable arm and the main beam are connected with the fixed seat through a movable bolt 111; the first sub-movable arm can rotate around the movable bolt and can rotate around the axial direction of the main beam; the movable arm further comprises a second sub-movable arm 102; the first end of the second sub-movable arm is fixedly mounted with the slide carriage 119; the top of the sliding seat is connected with the second sub-movable arm through a movable bolt; the second end of the second sub-movable arm and the middle section of the first sub-movable arm are installed in a matched manner by adopting a group of electric slide rails 115, so that the second end of the second sub-movable arm can perform sliding movement on the first sub-movable arm;

further, the bottom of the slide comprises a plurality of moving wheels 105; the plurality of moving wheels is preferably a universal wheel, as shown in fig. 3; each moving wheel is driven by a micro motor and a speed changer; the motor is preferably a coded motor; the coding motor can be independently controlled by the control module to rotate, output torque and rotate speed; the coding motor has a brake self-locking function, and can ensure that the output shaft does not rotate reversely or slide when external torque acts on the output shaft of the coding motor;

further, each of the universal wheels includes a hub 301 and a plurality of rollers 302; said plurality of rollers being arranged around said hub for one revolution and each of said rollers being free to rotate; furthermore, the central axes of the rollers and the central axis of the hub form an included angle phi; furthermore, the movable wheels on the left side and the right side of the sliding seat are arranged in a mirror symmetry mode, namely if the included angle of the universal wheels on the left side is phi, the included angle of the universal wheels on the right side is-phi; as shown in fig. 4, taking four sets of the moving wheels as an example, the sliding seat can be moved in four directions according to the turning directions of the moving wheels; if the steering direction when the moving wheel is viewed from the outside is set as a stated turning direction, the following directions are set:

advancing: first left-counterclockwise, second left-counterclockwise, first right-clockwise, second right-clockwise;

retreating: first-clockwise left, second-clockwise left, first-counterclockwise right, second-counterclockwise right;

left translation: first-clockwise left, second-counterclockwise left, first-clockwise right, second-counterclockwise right;

and (3) right translation: first left-counterclockwise, second left-clockwise, first right-counterclockwise, second right-clockwise;

according to the steering setting of the four groups of moving wheels, the sliding seat can move on the main beam in four directions;

further, the slide includes a hoop 118; the hoop surrounds the main beam and is connected with the sliding seat to ensure that the sliding seat can not fall off when moving on the main beam; preferably, the rollers on the moving wheel are made of rubber, silica gel or other high-friction materials; through the configuration of the materials, the sliding base can be kept stable and static on the main beam;

further, the movable arm includes a third sub-movable arm 103; the middle section of the third sub-movable arm is connected with the second end of the first sub-movable arm through a movable bolt 112, and the second end of the third sub-movable arm is connected with the second sub-movable arm by using a first telescopic electric cylinder 116; the first telescopic electric cylinder 116 can be telescopic along the self axial direction, so that the third sub-movable arm swings around the movable bolt 112;

further, the movable arm further includes a fourth sub-movable arm 104; the first end of the third sub-movable arm is connected with the middle section of the fourth sub-movable arm through a movable bolt; meanwhile, the second end of the fourth sub-movable arm is connected with the middle section of the third sub-movable arm by using a second telescopic electric cylinder 117; the second telescopic electric cylinder can be telescopic along the self axial direction, so that the fourth sub-movable arm swings around the movable bolt 112;

through the above combination mode, the first sub-movable arm, the second sub-movable arm, the third sub-movable arm and the fourth sub-movable arm form a group of multi-link structure, and through the linear displacement generated by the slide seat, the first telescopic electric cylinder, the second telescopic electric cylinder and the electric slide rail, the movable arm is made to extend and retract, and the reachable range of the movable end is made to cover most positions of the head of a user.

Example two:

this embodiment should be understood to include at least all of the features of any of the foregoing embodiments and further modifications thereon; an intelligent breathing abnormality detection system, comprising: the device comprises a movable arm, a tracking module, a detection module and a control module; the movable arm comprises a main beam fixed on the bed and a movable end positioned at the farthest end of the movable arm; the tracking module is arranged above the head of a user in an inclined manner, the position coordinate recognition is carried out by tracking the target position of the face of the user by using the sensor, and the recognized position coordinate is uploaded to the control module; the detection module is arranged at the moving end of the movable arm and detects the breathing gas along with the movement of the moving end to a target position; the control module is in communication connection with the movable arm, the tracking module and the detection module; the control module sends a driving instruction to move the movable arm according to the position coordinate identified by the tracking module, and starts respiration monitoring after the detection module is placed at a proper position in front of the nose of a user;

the tracking module adopts a photoelectric night vision sensor as a main vision acquisition element; the detection system firstly adopts the tracking module to scan and collect face images of the face of the user; the photoelectric night vision sensor detects the characteristic quantity of each part of the face of a user in a grid dividing mode, digitalizes the characteristic quantity of the face information of the user, stores the digitalized characteristic quantity in the control module and focuses on the nose area of the user; when the position and the posture of the face of a user change during sleeping, the control module determines the position coordinates of the nose of the user and drives the moving end to move towards the position coordinates of the nose;

the movable arm comprises a plurality of sub-movable arms; one end of each of the two sub movable arms is connected through a movable joint, so that the two sub movable arms rotate around the movable joint at one end of each sub movable arm in at least one degree of freedom; at least one section of the sub-movable arm is provided with a group of link mechanisms and a driver, and the sub-movable arm is driven to rotate around the movable joint at one end of the sub-movable arm;

the driver includes at least one of: the device comprises a hydraulic cylinder, an electric slide rail and a motor assembly;

the photoelectric night vision sensor is used for collecting the face information of a user in a low-light environment; the tracking module comprises a visual computing system; the vision operation system can process the facial optical information acquired by the photoelectric night vision sensor into digital information, and converts the digital information into coordinate information which can be digitally described through conversion;

the coordinate information of the visual operation system comprises coordinate information of a target object on an imaging plane and depth information of the target object on a visual depth;

the detection module comprises a sound sensor; the sound sensor collects sound information in the breathing process of a user, converts the sound information into digital information and uploads the digital information to the control module; the sound information collected by the sound sensor comprises sound volume, sound frequency and sound noise;

the detection module comprises a gas composition analyzer; the gas component analyzer collects and analyzes the exhaled gas of a user; the gas component analyzer is used for analyzing the component content of at least one of the following substances in gas: oxygen, nitrogen, carbon dioxide, carbon oxides, oxygen-containing organic compounds;

the system for intelligently detecting the respiratory abnormality comprises the following target object tracking algorithm:

s1: the tracking module acquires the coordinate position (x, y, z) of the nose of a user, wherein x and y are plane position coordinates, and z is a depth position coordinate;

s2: judging an included angle theta between the face orientation of the user and the vertical direction;

s3: driving the movable arm to move, and moving the moving end to (x, y, z + h), wherein h is a monitoring distance, and an included angle between the moving end and the vertical direction is theta;

s4: starting the detection module to perform pre-acquisition, and determining whether the numerical value of the acquired information reaches the threshold value of the lowest analysis amount;

s5: if the threshold value of the minimum analysis amount is reached, entering conventional collection; if the minimum analysis amount threshold value is not reached, confirming the target position again, and repeating the algorithm steps from S1 to S4;

the tracking module is arranged at the bottom of the main beam; the tracking module comprises at least one lens group; the lens group is provided with a plurality of imaging lenses; the plurality of imaging lenses at least comprise a wide-angle lens, and the wide-angle lens is used for enabling the observation view angle of the tracking module to be more than 150 degrees; the imaging lenses at least comprise a filter lens used for filtering light of ambient incident light based on light wavelength; the plurality of imaging lenses at least comprise a group of zoom lens groups; the zoom lens group comprises a plurality of zoom lenses; the zoom lens group further comprises at least one automatic zoom ring; the automatic zooming ring is driven by an internal micromotor to change the mutual distance of all the zooming lenses in the zooming lens group; enabling the tracking module to carry out focusing shooting on positions with different distances in a visual field;

the tracking module comprises a photoelectric night vision sensor; the photoelectric night vision sensor is arranged at the rear end of the imaging lens group; in the extremely weak light environment, the object still can reflect light rays with various wavelengths, including visible light and invisible light, especially lower part in the infrared spectrum; when the part of the light passes through the filter of the lens group in a reflecting way, the filter lens filters light with a specific wavelength in a spectrum and allows the filtered light of a part of spectrum channels to pass through the filter; the filtered light further enters a photoelectric cathode on the photoelectric night vision sensor, energy electrons are generated by utilizing the photoelectric effect of a photoelectric sensor, and the energy of the generated electrons is increased by the photoelectric cathode through high-voltage processing, so that the detectability of the electrons is amplified; further, the released electrons of the photocathode enter a fluorescent lens with a fluorescent coating, and fluorescent particles on the fluorescent lens are excited to release photons with specific energy at specific spectral positions; in the process, electrons released by the photocathode have initial kinetic energy after being processed by high voltage, and the distance passed by the photocathode in the subsequent movement process is extremely short and the movement direction of the electrons is kept by a high-voltage electric field in the process; so that photons excited on the fluorescent coating substantially retain the image profile characteristic described by the original electrons; finally, intercepting photons through an imaging sensor and forming an observable image; the photoelectric night vision sensor is connected with the visual operation system through a circuit, and the image information is processed by the visual operation system and then fed back to the control module in a digital signal form;

further, the tracking module comprises a set of laser ranging sensors; the laser ranging utilizes invisible laser to carry out fixed-point ranging, and feeds the distance of a target point back to the control module;

further, the control module comprises a set of image recognition algorithms; before the user uses the detection system, the tracking module is used for carrying out image pre-acquisition for multiple times, and normal using environment conditions such as illuminance and a visual field range are simulated; the image recognition algorithm obtains the facial features of a user in a machine learning mode for pre-collected image information, and performs vertex transformation on the facial features by using a vertex algorithm of a quadrilateral mesh or a triangular mesh so as to obtain a plurality of feature points; the image recognition algorithm endows three-dimensional coordinate information of a plurality of feature points;

further, the operator specifies the range of the plurality of feature points manually or by an algorithm, specifies the feature points of the nose and mouth of the user, and the image recognition algorithm performs a plurality of image recognition operationsThe image recognition learning is carried out, the image processing capability for recognizing the nose and the mouth of the user is obtained, and the n characteristic point coordinates of the nose and the mouth after being recognized are marked as target characteristic coordinates (x)₁,y₁,z₁)、(x₂,y₂,z₂)……(x_n,y_n,z_n) (ii) a The image recognition algorithm can adopt the existing image recognition algorithm, and is not described herein again;

furthermore, a user uses the tracking module to shoot images of a plurality of facial angles of the user, including the front, two side surfaces or a part covered by a quilt, and obtains the capability of correctly identifying the position coordinates of the nose and the mouth of the user under various facial angles through a plurality of machine learning of the image identification algorithm;

furthermore, the control module drives the movable arm to move, the detection module is placed at the nose and mouth positions of the user, and exhaled air monitoring is carried out.

Example three:

this embodiment should be understood to include at least all of the features of any of the embodiments described above and further refinements thereto: an intelligent breathing abnormality detection system, comprising: the device comprises a movable arm, a tracking module, a detection module and a control module; the movable arm comprises a main beam fixed on the bed and a movable end positioned at the farthest end of the movable arm; the tracking module is arranged above the head of a user in an inclined manner, the position coordinate recognition is carried out by tracking the target position of the face of the user by using the sensor, and the recognized position coordinate is uploaded to the control module; the detection module is arranged at the moving end of the movable arm and detects the breathing gas along with the movement of the moving end to a target position; the control module is in communication connection with the movable arm, the tracking module and the detection module; the control module sends a driving instruction to move the movable arm according to the position coordinate identified by the tracking module, and starts respiration monitoring after the detection module is placed at a proper position in front of the nose of a user;

the tracking module adopts a photoelectric night vision sensor as a main vision acquisition element; the detection system firstly adopts the tracking module to scan and collect face images of the face of the user; the photoelectric night vision sensor detects the characteristic quantity of each part of the face of a user in a grid dividing mode, digitalizes the characteristic quantity of the face information of the user, stores the digitalized characteristic quantity in the control module and focuses on the nose area of the user; when the position and the posture of the face of a user change during sleeping, the control module determines the position coordinates of the nose of the user and drives the moving end to move towards the position coordinates of the nose;

the movable arm comprises a plurality of sub-movable arms; one end of each of the two sub movable arms is connected through a movable joint, so that the two sub movable arms rotate around the movable joint at one end of each sub movable arm in at least one degree of freedom; at least one section of the sub-movable arm is provided with a group of link mechanisms and a driver, and the sub-movable arm is driven to rotate around the movable joint at one end of the sub-movable arm;

the driver includes at least one of: the device comprises a hydraulic cylinder, an electric slide rail and a motor assembly;

the photoelectric night vision sensor is used for collecting the face information of a user in a low-light environment; the tracking module comprises a visual computing system; the vision operation system can process the facial optical information acquired by the photoelectric night vision sensor into digital information, and converts the digital information into coordinate information which can be digitally described through conversion;

the coordinate information of the visual operation system comprises coordinate information of a target object on an imaging plane and depth information of the target object on a visual depth;

the detection module comprises a sound sensor; the sound sensor collects sound information in the breathing process of a user, converts the sound information into digital information and uploads the digital information to the control module; the sound information collected by the sound sensor comprises sound volume, sound frequency and sound noise;

the detection module comprises a gas composition analyzer; the gas component analyzer collects and analyzes the exhaled gas of a user; the gas component analyzer is used for analyzing the component content of at least one of the following substances in gas: oxygen, nitrogen, carbon dioxide, carbon oxides, oxygen-containing organic compounds;

the system for intelligently detecting the respiratory abnormality comprises the following target object tracking algorithm:

s1: the tracking module acquires the coordinate position (x, y, z) of the nose of a user, wherein x and y are plane position coordinates, and z is a depth position coordinate;

s2: judging an included angle theta between the face orientation of the user and the vertical direction;

s3: driving the movable arm to move, and moving the moving end to (x, y, z + h), wherein h is a monitoring distance, and an included angle between the moving end and the vertical direction is theta;

s4: starting the detection module to perform pre-acquisition, and determining whether the numerical value of the acquired information reaches the threshold value of the lowest analysis amount;

s5: if the threshold value of the minimum analysis amount is reached, entering conventional collection; if the minimum analysis amount threshold value is not reached, confirming the target position again, and repeating the algorithm steps from S1 to S4;

in this embodiment, the detection system includes a control method for adjusting the depth of intervention into a user's sleep stage; after the tracking module successfully confirms the positions of the nose and the mouth of the user at a time, the control module drives the movable arm, the detection module is started after being moved to the positions of the nose and the mouth of the user, and the characteristic quantities of breathing sound of the user, including a sound decibel value L and a sound frequency f, are collected through the sound module; the control module establishes a time curve for the collected sound characteristic quantity, and forms a characteristic equation through statistics of a plurality of characteristic points on the time curve, wherein the characteristic equation comprises the following steps:

1. at t₁、t₂......t_nAt all times, obtaining a plurality of sound decibel values L₁、L₂......L_nObtaining a characteristic equation L (t) related to decibel value-time;

2. at t₁、t₂......t_nObtaining a plurality of frequency values f of breath sounds at any moment₁、f₂......f_nObtaining a characteristic equation f (t) related to frequency-time;

as shown in fig. 6, the period T of the user's breath is obtained by counting a plurality of peaks and troughs of the characteristic equation curve; further, a plurality of periods T obtained in the acquisition₁、T₂......T_nIn which a plurality of decibel values of sound are marked at the same time in different periods, e.g. at T₁A plurality of moments T within a cycle_{1_1}、T_{1_2}......T_{1_n}In the middle, corresponding to a plurality of sound decibel values L_{T1_1}、L_{T1_2}......L_{T1_n}And a plurality of sound frequency values f_{T1_1}、f_{T1_2}......f_{T1_n}(ii) a Further, in the period T_kThen, calculating the average value and the standard deviation value of the sound decibel value and the sound frequency value of a plurality of same time points m of j breathing cycles before the current breathing cycle, namely:

calculating the average sound decibel value at the moment m according to a formula 1;

calculating the average value of the sound frequency values at the moment m according to a formula 2;

calculating a sound decibel value standard difference value of the moment m according to a formula 3;

calculating a standard difference value of the sound frequency value at the moment m according to a formula 4;

by the above formulas 1-4, the evaluation is performed in the period T_kAbnormal change of sound decibel value and sound frequency value at a certain moment relative to the previous j periodsDegree of deviation in time;

furthermore, through clinical experiments, a plurality of sound characteristic sample values of the user in the sleep stage are measured, and a plurality of inter-sound decibel value standard deviation threshold values including a deep layer threshold value P are calculated₀Shallow threshold value P₁And a warning threshold value P₂Corresponding to a decibel value of L_p0，L_p1，L_p2And L is_p0<L_p1<L_p2According to S_Lk-mDetermining a plurality of operating modes of the detection system if the value of (a) exceeds a threshold for a certain stage, comprising:

when S is less than or equal to P₀When the current user is in a stable state, the detection system adjusts the tracking and monitoring interval period of the tracking module and the detection module to 5 minutes or longer; adjusting the target position coordinate of the tracking module movement to (x, y, z + h '), wherein the monitoring distance h' can be set to 0.2 meter; the purpose of adjusting the detection system in this state is to enable the movable arm and the detection module to reduce the working frequency and reduce the influence on the sleep of the user;

when P is present₀≤S≤P₁The current user is in a first active state; the detection system adjusts the tracking and monitoring interval period of the tracking module and the detection module to 1 minute; the monitoring distance h is not adjusted;

when P is present₁≤S≤P₂The current breathing of the user is in an unstable state, and abnormal breathing accidents can happen; the detection system can wake up a user or call other people for early warning operation according to the program setting of an actual technician so as to prevent possible accidents;

the above description only describes the judgment algorithm based on the two sound characteristic parameters of the sound decibel value and the sound frequency value, and other sound characteristic parameters collected by the detection module may also be calculated by using a similarity principle algorithm, which is not described in detail in this embodiment.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.

Although the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the invention. That is, the methods, systems, and devices discussed above are examples. Various configurations may omit, substitute, or add various procedures or components as appropriate. For example, in alternative configurations, the methods may be performed in an order different than that described, and/or various components may be added, omitted, and/or combined. Moreover, features described with respect to certain configurations may be combined in various other configurations, as different aspects and elements of the configurations may be combined in a similar manner. Further, elements therein may be updated as technology evolves, i.e., many elements are examples and do not limit the scope of the disclosure or claims.

Specific details are given in the description to provide a thorough understanding of the exemplary configurations including implementations. However, configurations may be practiced without these specific details, for example, well-known circuits, processes, algorithms, structures, and techniques have been shown without unnecessary detail in order to avoid obscuring the configurations. This description provides example configurations only, and does not limit the scope, applicability, or configuration of the claims. Rather, the foregoing description of the configurations will provide those skilled in the art with an enabling description for implementing the described techniques. Various changes may be made in the function and arrangement of elements without departing from the spirit or scope of the disclosure.

In conclusion, it is intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that these examples are illustrative only and are not intended to limit the scope of the invention. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.