Intelligent nursing mattress system

Abstract

According to the intelligent nursing mattress system, a biological radar and a pressure / temperature and humidity sensor array are integrated on a mattress, body pressure distribution, respiratory rate and body position data are monitored in real time, an optimal turning-over path is dynamically planned through a reinforcement learning model, and the pressure of a contact surface is optimized in combination with a pressure compensation algorithm. The system can realize four core functions: multi-stage bedsore prevention, breathing assistance, intelligent excretion nursing and muscular atrophy prevention; the priority of each mode is coordinated through a mutual exclusion control unit, Internet of Things communication and remote strategy updating are supported, all-weather self-adaptive adjustment is carried out to improve body pressure distribution and breathing states, and the system is suitable for comprehensive nursing of long-term bedridden patients.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home and medical care equipment, in particular to a smart nursing mattress system. BACKGROUND

[0002] Long-term bedridden patients generally face clinical problems such as bedsores, muscle atrophy, decreased respiratory function, and excretion care difficulties. Traditional nursing mattress has the following defects: 1) static air cushion is mostly used, which can only relieve pressure by periodic pressure release, and lacks targeted bed sore prevention; 2) respiratory abnormalities rely on artificial monitoring, and lack active intervention mechanism; 3) excretion processing needs artificial discovery and processing, and the timeliness is poor.

[0003] Therefore, it is necessary to provide a smart nursing mattress system to solve the problems mentioned in the background. SUMMARY

[0004] To achieve the above purpose, the present application provides the following technical scheme: a smart nursing mattress system, comprising: a data acquisition module for acquiring pressure distribution data on the surface of the mattress and user physiological index data in real time, wherein the physiological index data at least includes respiratory rate, body movement signal and excretion trigger signal; An intelligent control module is signal connected with the data acquisition module, and based on the pressure data, the user body position state is identified, the physiological index data triggers multi-mode operation instruction or alarm signal; An execution module is used for receiving the multi-mode operation instruction issued by the intelligent control module; A communication module is used for realizing data interaction between the intelligent control module and the data acquisition module and the execution module; The execution module comprises: a multi-axis adjustment unit, a pressure release unit, a back patting unit and an excretion care unit which are signal connected with the intelligent control module respectively, and the execution module triggers the following modes based on the received multi-mode operation instruction: When the local pressure of the mattress is greater than 32mmHg and lasts for more than or equal to 2 hours, a multi-stage composite bed sore prevention mode is triggered based on pressure compensation algorithm; When the user's respiratory rate is greater than 30 times per minute and the duration is greater than or equal to 5 minutes, a respiratory assistance mode is triggered; When the excretion event is detected, an intelligent excretion care mode is triggered; Based on the body position keeping time greater than 4 hours, a muscle atrophy prevention mode is automatically triggered; A mutual exclusion control unit is used for priority sorting when there is conflict between modes.

[0005] Preferably, the multi-axis adjustment unit comprises: A back-raising mechanism is arranged at either end of the length direction of the mattress and used to adjust the back-raising angle of the mattress; A turning mechanism is symmetrically arranged at both sides of the length direction of the mattress and used to adjust the turning angle of the mattress; The intelligent control module constructs a reinforcement learning model based on the user's body weight distribution, body position holding time and physiological indicators, and dynamically plans an optimal turning path based on the reinforcement learning model.

[0006] Preferably, the reinforcement learning model takes the incidence of bedsores, comfort score and turning time as optimization targets, and outputs the turning angle, back-raising angle and patting frequency parameters.

[0007] Preferably, the pressure relief unit includes a plurality of independently controlled air bag groups uniformly arranged on the top of the mattress, each air bag group includes a plurality of uniformly arranged air bag units, and the air bag units in each air bag group are connected. The multi-stage composite anti-bedsores mechanism includes: S1.1, periodically inflate and deflate the air bag group in the pressure abnormal area based on the data collected by the data acquisition module; S1.2, simultaneously control the back patting unit to perform horizontal patting vibration; S1.3, control the multi-axis adjustment unit to automatically turn at a 12-18° inclination angle to improve pressure distribution.

[0008] Preferably, the back patting unit includes: A plurality of patting blocks are arranged in the direction of the spine and embedded in the top of the mattress and correspond to the user's back area, the bottom of the patting block is provided with a driving mechanism, the driving mechanism is used to drive the patting block to reciprocatingly lift and pat the user's back, and each patting block performs wave-shaped patting massage on the user's back in a specific time sequence and direction.

[0009] Preferably, the breathing assistance mode includes: S2.1, control the back-raising mechanism to lift the back area of the mattress to 10-55°; S2.2, control the pressure relief unit to reduce the air pressure of the air bag in the user's hip area by 18-22% of the inflation air pressure; S2.3, start the back patting unit to perform longitudinal patting vibration.

[0010] Preferably, the excretion care unit includes: A bedpan is embedded and installed on the mattress, a collection bin is installed at the bottom end of the bedpan, and a detection subunit is arranged in the bedpan to identify excretion events. An electrically-powered excrement collecting valve is sealingly installed at the bottom of the toilet bowl and the entrance of the collecting bin, for guiding the excrement into the collecting bin; A cleaning module and a drying module are installed in the toilet bowl, for performing warm water flushing and hot air drying on the user and the toilet bowl after excretion; The detection subunit is further configured to detect that the user cleaning area and the toilet bowl reach a preset cleaning standard, and then turn off each execution unit.

[0011] Preferably, when the detection subunit detects excretion, the intelligent excretion care mode is started; The intelligent excretion care mode comprises: S3.1, control the electrically-powered excrement collecting valve to open, and guide the excrement into the collecting bin; S3.2, start the cleaning module to perform warm water flushing on the user and the toilet bowl; S3.3, perform hot air drying on the user and the toilet bowl after flushing; S3.4, detect that the user cleaning area and the toilet bowl reach a preset cleaning standard, and then turn off each execution unit.

[0012] Preferably, the muscle atrophy prevention mode comprises: S4.1, based on the pressure distribution data, periodically inflate and deflate the air bag in the pressure area; S4.2, and start the back patting unit to perform patting massage.

[0013] Preferably, the communication module is further configured to: interact with external devices to transmit physiological data and alarm signals, and receive user configuration instructions; or remote update of the care strategy database; or data interaction with a medical monitoring platform based on an Internet of Things communication protocol.

[0014] Compared with the prior art, the present application provides an intelligent care mattress system, which has the following beneficial effects: In the present application, through multi-source data fusion and reinforcement learning model, four core functions are integrated: a multi-level pressure sore prevention mechanism based on pressure compensation algorithm and dynamic turning-over planning, combined with biological radar to realize three-level intervention of respiratory abnormalities, equipped with an automatic excretion care unit and a muscle atrophy prevention unit, through environmental perception and adaptive control, all-weather optimization of user body pressure distribution and respiratory state, while supporting remote data interaction, significantly improving the care quality and comfort of long-term bedridden patients. BRIEF DESCRIPTION OF DRAWINGS

[0015] Fig. 1 It is a module interaction flowchart of an intelligent care mattress system; Fig. 2 It is a multi-mode trigger logic flowchart of an intelligent care mattress system; In the figure: 1, data acquisition module; 2, intelligent control module; 3, communication module; 4, mutual exclusion control unit; 5, execution module; 6, multi-axis adjustment unit; 7, pressure relief unit; 8, excretion nursing unit; 9, back patting unit. DETAILED DESCRIPTION

[0016] The present application provides an intelligent nursing mattress system, which realizes four core functions of multi-level composite pressure sore prevention function, breathing assistance function, intelligent excretion nursing function and muscle atrophy prevention function through multi-source data fusion and reinforcement learning strategy, so as to solve the prevention and treatment of pressure sores, muscle atrophy, and the decline of respiratory function and the inability to self-care excretion of long-term bedridden patients.

[0017] Referring to Figs. 1-2 The present application provides an intelligent nursing mattress system, which comprises: A data acquisition module 1 is used for acquiring pressure distribution data on the surface of the mattress and user physiological index data in real time, wherein the physiological index data at least includes respiratory frequency, body movement signal and excretion trigger signal; The data acquisition module 1 at least includes a biological radar sensor, temperature, humidity and pressure sensors, a timer and the like. The biological radar sensor is integrated in the mattress and is used for monitoring user respiratory frequency and heart rate data. The temperature, humidity and pressure sensors are evenly arranged on the surface layer of the mattress and are used for monitoring user body temperature, body position state and body position keeping time and the like.

[0018] An intelligent control module 2 is in signal connection with the data acquisition module 1 and identifies user body position state based on pressure data and triggers multi-mode operation instructions or alarm signals based on physiological index data; An execution module 5 is used for receiving multi-mode operation instructions issued by the intelligent control module 2; A communication module 3 is used for realizing data interaction between the intelligent control module 2 and the data acquisition module 1 and the execution module 5; The execution module 5 comprises a multi-axis adjustment unit 6, a pressure relief unit 7, a back patting unit 9 and an excretion nursing unit 8 which are in signal connection with the intelligent control module 2 respectively, and the execution module 5 triggers the following modes based on received multi-mode operation instructions: When the local pressure of the mattress is greater than 32mmHg and lasts for greater than or equal to 2 hours, a multi-level composite pressure sore prevention mode is triggered based on a pressure compensation algorithm; When the respiratory frequency of the user is greater than 30 times per minute and the duration is greater than or equal to 5 minutes, a breathing assistance mode is triggered; When an excretion event is detected, an intelligent excretion nursing mode is triggered; A muscle atrophy prevention mode is automatically triggered based on body position keeping time greater than 4 hours; A mutual exclusion control unit 4 is configured to prioritize the modes when there is a conflict between the modes.

[0019] Specifically, when the excretion care mode and the pressure sore prevention mode conflict, the excretion care mode is prioritized, and when the respiratory assistance mode and the pressure sore prevention mode need to be responded to simultaneously, the back patting action required by the respiratory assistance mode is prioritized.

[0020] In this embodiment, the multi-axis adjustment unit 6 includes: A back raising mechanism is arranged at either end of the mattress in the length direction of the mattress and serves to adjust the back raising angle of the mattress, the back raising angle adjustment range being 0°-80°; the back raising mechanism adopts a servo motor push rod structure to adjust the back raising angle. A turning mechanism is symmetrically arranged at both sides of the mattress in the length direction of the mattress and serves to adjust the turning angle of the mattress, the turning angle adjustment range being 0°-55°; the turning mechanism adopts a synchronous lifter for turning angle control. The intelligent control module 2 constructs a reinforcement learning model based on the user weight distribution, body position holding time and physiological indicators and dynamically plans an optimal turning path based on the reinforcement learning model.

[0021] The reinforcement learning model construction method includes: a. Environment modeling: an environment model containing state transition probability and immediate reward function is established, a Markov decision process framework (MDP) is constructed through interactive data collection, and for complex scenes, a model-independent method can be used to directly learn a strategy function.

[0022] b. Definition of state and action space: the state space definition needs to include environmental observation variables, including user weight distribution, body position holding time, respiratory rate and pressure distribution data, etc.; the action space definition decides the output dimension, including turning angle, back raising angle and patting frequency, etc., which together constitute the input and output structure of the strategy network; c. Reward mechanism design: the learning direction is guided by designing an immediate reward function, and a sparse reward, a hierarchical reward or a reward modeling method based on artificial feedback can be used; taking the reduction of pressure sore incidence, user comfort score and turning time consumption as the optimization target, the turning angle, back raising angle and patting frequency parameters are output to dynamically adjust the path planning strategy; d. Strategy network architecture: a deep neural network is constructed as a strategy function approximator, common structures include: value network: evaluating the long-term returns of state / action pairs; strategy network: directly outputting action probability distribution.

[0023] Model training: based on historical care data, iterative optimization is performed.

[0024] Further, the pressure relief unit 7 comprises a plurality of independent control air bag groups uniformly arranged on the top of the mattress, each of the pressure air bag groups comprises a plurality of uniformly arranged air bag units, the air bag units in each of the air bag groups are communicatively arranged, the pressure adjustment range of each of the air bag units is 5-120mmHg, and the air bag units are in honeycomb structure or square structure, etc. The multi-stage composite anti-bedsore mechanism comprises: S1.1, periodically inflating and deflating the air bag group in the pressure abnormal area based on the data collected by the data acquisition module 1, and the deflation period is 5 minutes; S1.2, simultaneously controlling the back patting unit 9 to perform transverse patting vibration, the transverse patting is patting at the same patting frequency as a row of patting blocks along the width direction of the mattress, and each row of patting blocks can be at different patting frequencies; S1.3, controlling the multi-axis adjustment unit 6 to perform 12-18° lateral angle automatic turning over to improve the pressure distribution.

[0025] Specifically, in the reinforcement learning application related to the physical system, the pressure compensation algorithm is implemented in the following ways: State space expansion: integrate the pressure parameters (current value, deviation) into the environment observation variables, construct a multi-dimensional observation space (such as St=[X t , P t , ΔP t ]), and realize real-time monitoring of pressure.

[0026] Reward function modification: design a compensation reward term: R comp =K p |Δp| -1 , where K p is a compensation coefficient, and Δp is a penalty for pressure deviation; Dynamic model integration: in model-based reinforcement learning (MBRL), integrate the pressure dynamic equation P t+1 =f(P t , a t )+E P , combine model predictive control (MPC) to realize feedforward compensation, and improve the prediction ability of the system to pressure changes; Adaptive policy adjustment: use a meta-reinforcement learning framework to enable the policy network to adjust compensation parameters (such as θ p =Φ(ΔP t )) online according to real-time pressure deviation ΔP t , and realize dynamic pressure management.

[0027] This method system has been verified in industrial control system optimization, and through the state association and reward modification of the pressure parameters, the robustness of the system can be effectively improved.

[0028] Further, the back patting unit 9 comprises: A plurality of patting blocks arranged in the direction of the spine and embedded on the top of the mattress corresponding to the back area of the user, the bottom of the patting block is provided with a driving mechanism for driving the patting block to reciprocatingly lift and pat the back of the user, and each of the patting blocks performs wave-shaped patting massage on the back of the user in a specific time sequence and direction.

[0029] Specifically, by setting a specific time sequence difference between adjacent patting blocks, a vibration phase difference is formed between each adjacent patting block, thereby forming a wave-shaped patting path.

[0030] Further, the breathing assistance mode comprises: S2.1, control the back raising mechanism to lift the back area of the mattress to 10-55°; S2.2, control the pressure relief unit 7 to reduce the air pressure of the air bag in the hip area of the user by 18-22% of the inflation air pressure; S2.3, start the back patting unit 9 to perform longitudinal patting vibration, the longitudinal patting is the patting at the same patting frequency as a column of patting blocks along the length direction of the mattress, and each column of patting blocks can be at different patting frequencies.

[0031] It needs to be explained that the breathing assistance mode realizes non-contact breathing frequency monitoring through 60GHz biological radar technology, and the accuracy reaches ±0.5 times / min. Different abnormal states are set: Respiratory slow: respiratory frequency <8 times / min.

[0032] Respiratory fast: respiratory frequency >30 times / min.

[0033] Apnea: single apnea is more than 10s, and the number of occurrences per hour is more than 5 times.

[0034] At the same time, different classification treatment schemes correspond to different abnormal breathing frequencies: When the respiratory slow occurs, a first-level alarm signal (SMS notification of the caregiver) is issued, at the same time, the back raising mechanism is controlled to lift the back area of the mattress to 10-20° to promote breathing; if there is no improvement after 5 minutes, the air bag in the hip area is intermittently deflated, each time the air pressure is 1% of the initial air pressure, the intermittent period is 3 minutes, the pressure is reduced, and the body burden is reduced. If there is still no improvement after 5 minutes, the back raising mechanism is controlled to lift the back area of the mattress to 30-45°, and the back patting unit 9 is started to perform longitudinal patting vibration, the frequency is set to 1-2Hz, to stimulate breathing.

[0035] When the respiratory rate is too fast, a secondary alarm signal (SMS notification of the caregiver + sound and light alarm) is sent out, the back raising mechanism is controlled to raise the back area of the mattress to 45° to improve the respiratory passage blockage; if there is no improvement after 1 min, the hip area air bag is deflated to reduce the air pressure by 30% to reduce the body compression; if there is still no improvement after 1 min, the back patting unit 9 is started to perform longitudinal patting vibration with a frequency of 2-3 Hz, which is synchronized with the respiratory rhythm to assist breathing.

[0036] When the respiratory pause occurs, a tertiary alarm signal (SMS notification of the caregiver + sound and light alarm + automatic emergency call) is sent out to notify the caregiver to intervene immediately, the back raising mechanism is controlled to raise the back area of the mattress to 55°, and longitudinal patting vibration is started at a frequency of 3-5 Hz to stimulate breathing.

[0037] In this embodiment, the excretion care unit 8 includes: A bedpan is embeddedly installed on the mattress, and a collection bin is installed at the bottom end of the bedpan. A detection subunit is arranged in the bedpan to identify excretion events, and the detection subunit at least includes a thin film pressure sensor, a temperature sensor, a humidity sensor, an odor sensor, etc. An electric pollution collection valve is sealingly installed at the bottom of the bedpan and the entrance of the collection bin to guide the excretion into the collection bin. A cleaning module and a drying module are installed in the bedpan to perform warm water flushing and hot air drying operations on the user and the bedpan after excretion. The detection subunit is also used to detect that the user cleaning area and the bedpan reach a preset cleaning standard, and then the execution units are closed.

[0038] Further, when the detection subunit detects that there is excretion, the intelligent excretion care mode is started. The intelligent excretion care mode includes: S3.1, the electric pollution collection valve is controlled to be opened to guide the excretion into the collection bin. S3.2, the cleaning module is started to perform warm water flushing on the user and the bedpan, the water temperature is 35℃±2℃, and the flow rate is 200ml / min. S3.3, after flushing, the user and the bedpan are dried by hot air, the air temperature is 40℃±10℃, the air speed is 30m / s, and the duration is 1-3 minutes. S3.4, after the user cleaning area and the bedpan reach a preset cleaning standard, the execution units are closed.

[0039] In this embodiment, the muscle atrophy prevention mode includes: S4.1, based on pressure distribution data, periodically inflate and deflate the airbag in the pressure area, pressure gradient 10-50 mmHg, frequency 0.8 Hz; S4.2, and start the back patting unit 9 to perform patting massage, amplitude 5-10 mm, frequency 1.5 Hz.

[0040] Specifically, the muscle atrophy prevention mode has a daily cumulative running time of greater than or equal to 0.5 hours, which can be adjusted according to the use comfort.

[0041] Further, the communication module 3 is also used for: interacting with external devices to transmit physiological data and alarm signals, and receiving user configuration instructions; or remote updating of the nursing strategy database; or data interaction with a medical monitoring platform based on an Internet of Things communication protocol.

[0042] In specific implementation, after the mattress is laid on the bed frame and self-checking is completed, user health information is input, the system automatically identifies body posture, heart rate and breathing frequency through pressure sensing and biological radar, dynamically adjusts the back lifting angle, turning posture and patting mode and marks personalized parameters; during the day (08:00-20:00), the timed intelligent excretion nursing mode, multi-stage composite bed sore prevention mode, breathing assistance mode and muscle atrophy prevention mode are executed; at night (20:00-08:00), the pressure response threshold is shortened, the vibration frequency and turning strategy are adjusted, and the excretion nursing and breathing intervention functions are simultaneously maintained, so as to improve the body pressure distribution, breathing state and blood circulation through adaptive adjustment all day long.

[0043] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can make equivalent replacement or change according to the technical solution and inventive concept of the present application within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A smart care mattress system, characterized in that, The application relates to a bed mattress with a multi-mode intelligent control system, which comprises the following parts: a data acquisition module (1) for acquiring pressure distribution data and user physiological index data on a bed mattress surface in real time, wherein the physiological index data at least includes respiratory frequency, body movement signals and excretion trigger signals; an intelligent control module (2) connected with the data acquisition module (1) and capable of identifying user body position states based on pressure data and triggering multi-mode operation instructions or alarm signals based on physiological index data; an execution module (5) for receiving multi-mode operation instructions sent by the intelligent control module (2); a communication module (3) for realizing data interaction between the intelligent control module (2) and the data acquisition module (1) and the execution module (5); the execution module (5) comprises a multi-axis adjustment unit (6), a pressure relief unit (7), a back patting unit (9) and an excretion nursing unit (8) connected with the intelligent control module (2) in signal mode, and the execution module (5) triggers the following modes based on received multi-mode operation instructions: when the local pressure of the bed mattress is greater than 32mmHg and lasts for more than or equal to 2 hours, a multi-stage composite anti-bedsores mode is triggered based on a pressure compensation algorithm; when the respiratory frequency of the user is greater than 30 times per minute and lasts for more than or equal to 5 minutes, a respiratory assistance mode is triggered; when an excretion event is detected, an intelligent excretion nursing mode is triggered; when the body position holding time is greater than 4 hours, a muscle atrophy prevention mode is automatically triggered; a mutual exclusion control unit (4) for performing mode priority sorting when conflicts exist between modes.

2. The smart nursing mattress system according to claim 1, wherein, the multi-axis adjustment unit (6) comprises: a back lifting mechanism arranged at any end of the bed mattress in the length direction and taking the hip and waist of the user as a boundary line, for adjusting the back lifting angle of the bed mattress; a turning mechanism symmetrically arranged on both sides of the bed mattress in the length direction, for adjusting the side turning angle of the bed mattress; wherein the intelligent control module (2) constructs a reinforcement learning model based on user weight distribution, body position holding time and physiological indexes, and dynamically plans an optimal turning path based on the reinforcement learning model.

3. The smart care mattress system of claim 2, wherein, the reinforcement learning model takes the bedsores incidence rate, the comfort score and the turning time consumption as optimization targets, and outputs the turning angle, the back lifting angle and the patting frequency parameters.

4. The smart nursing mattress system according to claim 1, wherein, the pressure relief unit (7) comprises a plurality of independently controlled air bag groups uniformly arranged on the top of the bed mattress, each air bag group comprises a plurality of uniformly arranged air bag units, and the air bag units in each air bag group are connected in communication; the multi-stage composite anti-bedsores mechanism comprises: S1.1, periodically inflating and deflating the air bag groups in the pressure abnormal area based on the data acquisition module (1) acquisition data; S1.2, simultaneously controlling the back patting unit (9) to perform horizontal patting vibration; S1.3, controlling the multi-axis adjustment unit (6) to perform 12-18 DEG side inclination angle automatic turning to improve the pressure distribution.

5. The smart care mattress system of claim 2, wherein, the back patting unit (9) comprises: a plurality of patting blocks arranged in an array along the spine direction and corresponding to the back area of the user on the top of the bed mattress, a driving mechanism is arranged at the bottom of each patting block, the driving mechanism is used for driving the patting block to reciprocatingly lift and pat the back of the user, and each patting block performs wave-shaped patting massage on the back of the user according to a specific time sequence and direction.

6. The smart care mattress system of claim 5, wherein, The breathing assistance mode comprises: S2.1, controlling the back-raising mechanism to raise the mattress back region to 10-55°; S2.2, controlling the pressure relief unit (7) to reduce the air pressure of the user's hip region air bag by 18-22% of the inflation air pressure; S2.3, starting the back patting unit (9) to perform longitudinal patting vibration.

7. The smart care mattress system of claim 1, wherein, The excretion care unit (8) comprises: a bedpan embeddedly installed on the mattress, a collection bin mounted at the bottom end of the bedpan, a detection subunit arranged in the bedpan for identifying excretion events; an electric pollution collection valve sealingly installed at the bottom of the bedpan and the entrance of the collection bin for guiding excrement into the collection bin; a cleaning module and a drying module installed in the bedpan for performing warm water flushing and hot air drying operations on the user and the bedpan after excretion; wherein the detection subunit is further configured to detect the user's cleaning area and the bedpan to reach a preset cleaning standard and then close each execution unit.

8. The smart care mattress system of claim 7, wherein, When the detection subunit detects excrement, the intelligent excretion care mode is started; The intelligent excretion care mode comprises: S3.1, controlling the electric pollution collection valve to open and guide excrement into the collection bin; S3.2, starting the cleaning module to perform warm water flushing on the user's local area and the bedpan; S3.3, performing hot air drying on the user's local area and the bedpan after flushing; S3.4, detecting the user's cleaning area and the bedpan to reach a preset cleaning standard and then closing each execution unit.

9. The smart nursing mattress system of claim 1, wherein, The muscle atrophy prevention mode comprises: S4.1, based on the pressure distribution data, periodically inflating and deflating the air bag in the pressure receiving area; S4.2, and starting the back patting unit (9) to perform patting massage.

10. The smart nursing mattress system of claim 1, wherein, The communication module (3) is further configured to: interact with external devices to transmit physiological data and alarm signals, and receive user configuration instructions; or remote update of the care strategy database; or data interaction with the medical monitoring platform based on the Internet of Things communication protocol.

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