Wearable nerve stimulation equipment intelligent control system

Abstract

The invention relates to the technical field of medical equipment, in particular to an intelligent control system for wearable nerve stimulation equipment, and the system comprises a data collection module which is used for collecting user heart rate data, user physiological data, environment data and equipment data; the heart rate feature analysis module is used for analyzing abnormal user behavior features; the behavior analysis module is used for analyzing abnormal user behavior features, and the physiological feature analysis module is used for analyzing user physiological features; the environment analysis module is used for analyzing the environment state and processing the analysis process of the physiological features of the user according to the analysis result; the control module is used for controlling the stimulation intensity of the equipment in the next monitoring period according to the analysis result of the abnormal behavior characteristics, the user physiological characteristics and the environment state in the monitoring period; and the output module is used for outputting the control result to a user. The control efficiency of the wearable nerve stimulation equipment is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical equipment, and in particular to an intelligent control system for wearable nerve stimulation equipment. Background Art

[0002] In recent years, the rapid development of wearable devices has made it possible to monitor users' physiological parameters in real time, which has provided new opportunities for personalized medical care and health management. Physiological data such as heart rate, blood oxygen saturation and skin conductivity can reflect an individual's health status and physiological response, and have become important indicators for assessing physical condition. However, the collection of a single parameter is often not enough to accurately reflect the user's overall health status, so a comprehensive analysis of multiple physiological data and environmental factors is required.

[0003] Chinese patent publication number CN109529193A discloses a vagus nerve stimulator and system based on closed-loop control, wherein the stimulator includes an acquisition unit for acquiring heart rate data in a patient's body; a communication unit for sending the heart rate data to an external device and receiving adjustable parameters fed back by the external device based on the patient's heart rate data over a period of time; and a control unit for determining a start threshold based on the adjustable parameters, and starting a stimulation action based on the start threshold and the patient's current heart rate data. It can be seen that this scheme only analyzes the heart rate data when controlling the vagus nerve stimulator, and there is a problem of low control efficiency of the nerve stimulation device. Summary of the invention

[0004] The object of the present invention is to provide an intelligent control system for a wearable neural stimulation device to solve at least one of the problems existing in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions: An intelligent control system for a wearable neural stimulation device, comprising: Data collection module, used to collect user heart rate data, user physiological data, environmental data and device data; A heart rate characteristic analysis module is used to construct a heart rate abnormality index based on the user's heart rate collected during the monitoring period; Behavior analysis module, used to analyze abnormal characteristics of user behavior based on heart rate abnormality index and collected RR interval; A physiological characteristic analysis module is used to analyze the abnormality of the user's conductivity and the abnormality of the user's blood oxygen saturation according to the user's skin conductivity and the user's blood oxygen saturation collected during the monitoring period, and analyze the user's physiological characteristics according to the analysis results; The environment analysis module is used to analyze the environment status according to the environmental noise and light intensity collected during the monitoring period, and to process the analysis process of the user's physiological characteristics according to the analysis results; A control module, which is used to control the stimulation intensity of the device in the next monitoring cycle according to the analysis results of the abnormal behavior characteristics, the user's physiological characteristics and the environmental status during the monitoring cycle, and to process the control process according to the device pulse width and the electrode surface area; The output module is used to output the control result of the stimulation intensity of the device in the next monitoring cycle to the user.

[0006] Furthermore, the heart rate characteristic analysis module is used to analyze the user's heart rate abnormality according to the user's heart rate a0 collected during the monitoring period and the preset heart rate threshold a1, the user's heart rate abnormality includes normal and abnormal, and construct a heart rate abnormality index XP according to the analysis result.

[0007] Further, the behavior analysis module is used to construct a heart rate fluctuation index according to the user's RR interval collected during the monitoring period to obtain a heart rate fluctuation coefficient B, and construct the heart rate fluctuation index according to the heart rate fluctuation coefficient B and a preset fluctuation coefficient b; The behavior analysis module analyzes the abnormal behavior characteristics of the user according to the heart rate abnormality index XP and the heart rate fluctuation index to obtain the abnormal behavior characteristics TX of the user.

[0008] Furthermore, the physiological characteristic analysis module includes a physiological state analysis unit, and the physiological state analysis unit is used to analyze the abnormality of the user's skin conductivity according to the user's skin conductivity d0 and the preset conductivity d1 collected during the monitoring period, and the abnormality of the user's skin conductivity includes normal and abnormal; The physiological state analysis unit is also used to analyze the abnormality of the user's blood oxygen saturation based on the user's blood oxygen saturation h0 collected during monitoring and the preset saturation h1. The abnormality of the user's blood oxygen saturation includes normal and abnormal.

[0009] Furthermore, the physiological characteristic analysis module also includes a physiological characteristic analysis unit, which analyzes the user's physiological state coefficient ST according to the analysis results of the user's conductivity abnormality and the user's blood oxygen saturation abnormality during the monitoring period, and analyzes the user's physiological state during the monitoring period according to the user's physiological state coefficient ST and a preset physiological state threshold value st0. The user's physiological state includes normal and abnormal. If the user's physiological state in the current monitoring period is normal, the user's physiological characteristics are set to SZ1; if the user's physiological state in the current monitoring period is abnormal, the user's physiological characteristics are set to SZ2.

[0010] Further, the environmental analysis module includes a data analysis unit, which is used to analyze the abnormality of the environmental noise according to the environmental noise z0 and the preset noise z1 collected during the monitoring period. The abnormality of the environmental noise includes normal and abnormal. If the environmental noise is normal, the noise abnormality coefficient is set to ZY1; if the environmental noise is abnormal, the noise abnormality coefficient is set to ZY2; The data analysis unit is also used to analyze the abnormality of light intensity based on the light intensity q0 collected during the monitoring period and the preset light intensity q1. The abnormality of light intensity includes normal and abnormal. If the light intensity is normal, the abnormality coefficient of light is set to GY1; if the light intensity is abnormal, the abnormality coefficient of light is set to GY2.

[0011] Further, the environment analysis module includes an environment analysis unit, which is used to analyze the environment state index HT according to the analysis results of the abnormality of the environment noise and the abnormality of the light intensity during the monitoring period, and analyze the environment state according to the environment state index HT and the preset environment state threshold ht, and the environment state includes normal and abnormal; The environment analysis unit processes the analysis process of the user's physiological characteristics when the environment state is abnormal, and sets the processed preset physiological state threshold value as st1.

[0012] Furthermore, the control module includes a control unit, which is used to control the stimulation intensity of the device in the next monitoring cycle according to the analysis results of the abnormal behavior characteristics, the user's physiological characteristics and the environmental status in the monitoring cycle, wherein: When the environmental state is normal, if TX-user physiological characteristics ≤ u0, the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F1; if TX-user physiological characteristics> u0, the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F2; When the environmental state is abnormal, if TX-user physiological characteristics ≤u0 / exp[-(HT-ht)], the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F3; if TX+user physiological characteristics>u0 / exp[-(HT-ht)], the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F4; Among them, u0 is the preset reference threshold.

[0013] Furthermore, the control module further comprises a pulse analysis unit, which analyzes the pulse state of the device according to the device pulse width m0 and the preset width m1, and the device pulse state includes a normal state and an abnormal state; The pulse analysis unit processes the control process of the stimulation intensity of the device when the pulse state of the device is an abnormal state, and sets the preset adjustment threshold after processing to f2.

[0014] Further, the control module further comprises an electrode analysis unit, which analyzes the abnormality of the electrode surface area according to the electrode surface area j0 and the preset surface area j1, and the abnormality of the electrode surface area includes normal and abnormal; The electrode analysis unit processes the analysis process of the device pulse state when the electrode surface area is abnormal, and adjusts the processed preset width to m1'.

[0015] The beneficial effects of the present invention are as follows: the wearable neural stimulation device intelligent control system can comprehensively evaluate the user's physiological state and the impact of the external environment on health by real-time monitoring of the user's heart rate, RR interval, blood oxygen saturation and skin conductivity, as well as environmental factors such as environmental noise and light intensity, so as to improve the efficiency of device control; secondly, the device stimulation intensity is intelligently adjusted to coordinate physiological data and environmental status, effectively improving the accuracy and safety of neural stimulation. This dynamic adjustment mechanism ensures that the user receives stimulation in the best physiological state and improves the efficiency of device control. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 Schematic diagram of the structure of the intelligent control system of the wearable neural stimulation device in this embodiment.

[0018] Figure 2 Schematic diagram of the structure of the physiological characteristic analysis module of this embodiment.

[0019] Figure 3 Schematic diagram of the structure of the environmental analysis module of this embodiment.

[0020] Figure 4 Schematic diagram of the structure of the control module of this embodiment. DETAILED DESCRIPTION

[0021] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0022] It should be noted that, although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0023] See also Figure 1 As shown, it is a schematic diagram of the structure of the intelligent control system of the wearable neural stimulation device of this embodiment, and the system includes: A data acquisition module is used to collect user heart rate data, user physiological data, environmental data and device data, wherein the user heart rate data includes the user heart rate and RR interval, wherein the RR interval is the time interval between two adjacent R waves in the user ECG, the user physiological data includes the user's blood oxygen saturation and the user's skin conductivity, the environmental data includes environmental noise and light intensity, and the device data includes electrode surface area, device pulse intensity and device stimulation intensity; in this embodiment, no specific limitation is made on the collection method of the user heart rate data, user physiological data, environmental data and device data, and those skilled in the art can freely set it, as long as the collection requirements of the user heart rate data, user physiological data, environmental data and device data are met, wherein the user heart rate data can use an ECG sensor combined with a photoelectric volumetric pulse wave sensor PPG to collect heart rate and RR interval, the blood oxygen saturation can be collected using a pulse oximeter, the skin conductivity can be collected using a skin conductivity sensor, the environmental data can be collected by an intelligent sensor, and the device data can be collected interactively.

[0024] Please continue reading Figure 1 As shown, the system also includes: A heart rate characteristic analysis module is connected to the data acquisition module. The heart rate characteristic analysis module is used to analyze the abnormality of the user's heart rate according to the user's heart rate a0 collected during the monitoring period and the preset heart rate threshold a1, and construct a heart rate abnormality index according to the analysis result, wherein: If a0≤a1, the heart rate characteristic analysis module determines that the user's heart rate is normal, otherwise, the heart rate characteristic analysis module determines that the user's heart rate is abnormal; The heart rate feature analysis module constructs a heart rate abnormality index XP according to the analysis results of the user's heart rate abnormality, and sets XP=k0 / K, where k0 is the duration of the user's heart rate abnormality within the monitoring period, and K is the duration of the monitoring period; the heart rate feature analysis module analyzes the abnormality of the user's heart rate according to a preset heart rate threshold, and constructs the heart rate abnormality index XP, which provides clear numerical support for quantitatively evaluating the degree of heart rate abnormality, thereby improving the accuracy of abnormal behavior feature analysis.

[0025] It can be understood that, in the present embodiment, there is no specific limitation on the setting of the preset heart rate threshold, and those skilled in the art can set it freely, as long as the setting requirements of the preset heart rate threshold are met, wherein the optimal value of the preset heart rate is 90 times / minute; in the present embodiment, there is no specific limitation on the setting of the monitoring period, and those skilled in the art can set it freely, as long as the setting requirements of the monitoring period are met, wherein the monitoring period can be set to 5 minutes, 10 minutes, etc.

[0026] Please continue reading Figure 1 As shown, the system also includes: A behavior analysis module is connected to the heart rate feature analysis module, and is used to construct a heart rate fluctuation index according to the user's RR interval collected during the monitoring period, and analyze the user's heart rate characteristics according to the heart rate abnormality index and the heart rate fluctuation index, wherein: The behavior analysis module constructs the heart rate fluctuation coefficient B according to the user's RR interval collected during the monitoring period, and sets: ; ri is the RR interval of the i-th user collected during the monitoring period, and I is the number of RR intervals of users collected during the monitoring period; The behavior analysis module constructs a heart rate fluctuation index according to the heart rate fluctuation coefficient B and the preset fluctuation coefficient b. If B≤b, the behavior analysis module sets the heart rate fluctuation index to bz1, setting bz1=0. Otherwise, the behavior analysis module sets the heart rate fluctuation index to bz2, setting bz2=Bb. The behavior analysis module analyzes the abnormal behavior feature TX of the user according to the heart rate abnormality index XP and the heart rate fluctuation index, and sets TX=lg(XP+1) / lg2+heart rate fluctuation index; the behavior analysis module evaluates the stability of the heart rate by calculating the heart rate fluctuation coefficient B, and provides a more comprehensive heart rate health profile in combination with the heart rate abnormality index and the heart rate fluctuation index, which can more effectively reflect the user's psychological and physiological stress.

[0027] It can be understood that the present embodiment does not specifically limit the setting of the preset fluctuation coefficient, and those skilled in the art can freely set it as long as the setting requirements of the preset fluctuation coefficient are met, wherein the optimal value of b is 0.1.

[0028] Please continue reading Figure 1 As shown, the system also includes: A physiological characteristic analysis module is connected to the data acquisition module, and is used to analyze the abnormality of the user's conductivity and the abnormality of the user's blood oxygen saturation based on the user's skin conductivity and blood oxygen saturation collected during the monitoring period, and analyze the user's physiological characteristics based on the analysis results.

[0029] See also Figure 2 As shown, the physiological characteristic analysis module includes: A physiological state analysis unit, used to analyze the abnormality of the user's skin conductivity according to the user's skin conductivity d0 collected during the monitoring period and the preset conductivity d1. If d0≤d1, the physiological state analysis unit determines that the user's skin conductivity is normal; if d0>d1, the physiological state analysis unit determines that the user's skin conductivity is abnormal; The physiological state analysis unit is also used to analyze the abnormality of the user's blood oxygen saturation based on the user's blood oxygen saturation h0 collected within the monitoring and the preset saturation h1. If h0≤h1, the physiological state analysis unit determines that the user's blood oxygen saturation is abnormal, otherwise, the physiological state analysis unit determines that the user's blood oxygen saturation is normal; by analyzing the skin conductivity and blood oxygen saturation, it is determined whether the user's physiological state is within the normal range, thereby improving the accuracy of the user's physiological characteristics analysis.

[0030] It can be understood that the setting of the preset conductivity and the preset saturation is not specifically limited in this embodiment, and those skilled in the art can set them freely as long as the setting requirements of the preset conductivity and the preset saturation are met, wherein the optimal value of d1 is 0.5 µS / cm, and the optimal value of h1 is 94%.

[0031] Please continue reading Figure 2 As shown, the physiological characteristic analysis module also includes: A physiological characteristic analysis unit connected to the physiological state analysis unit, wherein the physiological characteristic analysis unit analyzes the user's physiological state coefficient ST according to the analysis results of the abnormality of the user's conductivity and the abnormality of the user's blood oxygen saturation during the monitoring period, and sets ST=x1×k1 / K+x2×ln(7×k2 / K+1) / ln8; by constructing the user's physiological state coefficient ST, a quantitative physiological state comprehensive evaluation is provided, making health management more scientific; The physiological characteristic analysis unit analyzes the physiological state of the user in the monitoring period according to the user physiological state coefficient ST and the preset physiological state threshold value st0, and analyzes the user's physiological characteristics according to the analysis result. If ST≤st0, the physiological characteristic analysis unit determines that the physiological state of the user in the current monitoring period is normal, and sets the user's physiological characteristics to SZ1, setting SZ1=0; if ST>st0, the physiological characteristic analysis unit determines that the physiological state of the user in the current monitoring period is abnormal, and sets the user's physiological characteristics to SZ2, setting SZ2=exp[3×(ST-st0)-3]; the physiological characteristic analysis unit analyzes the physiological characteristics according to the physiological state analysis result to provide data support for the control of subsequent equipment, thereby improving the control efficiency of the equipment; Among them, x1 is the conductivity weight, x2 is the blood oxygen saturation weight, x1+x2=1, k1 is the duration of abnormal skin conductivity of the user during the monitoring period, and k2 is the duration of abnormal blood oxygen saturation of the user during the monitoring period.

[0032] It can be understood that, in this embodiment, there is no specific limitation on the setting of the preset physiological state threshold and each weight, and those skilled in the art can set them freely as long as the setting requirements of the preset physiological state threshold and each weight are met, among which the optimal value of x1 is 0.4, the optimal value of x2 is 0.6, and the optimal value of st0 is 0.2.

[0033] Please continue reading Figure 1 As shown, the system also includes: The environment analysis module is connected to the data acquisition module and the physiological characteristics analysis module. The environment analysis module is used to analyze the environmental status according to the environmental noise and light intensity collected during the monitoring period, and process the analysis process of the user's physiological characteristics according to the analysis results.

[0034] See also Figure 3 As shown, the environmental analysis module includes: A data analysis unit is used to analyze the abnormality of the environmental noise according to the environmental noise z0 collected during the monitoring period and the preset noise z1. If z0≤z1, the data analysis unit determines that the environmental noise is normal, and sets the noise abnormality coefficient to ZY1, setting ZY1=0; if z0>z1, the data analysis unit determines that the environmental noise is abnormal, and sets the noise abnormality coefficient to ZY2, setting ZY2=(z0-z1) / (z0+z1); The data analysis unit is also used to analyze the abnormality of light intensity based on the light intensity q0 collected during the monitoring period and the preset light intensity q1. If q0≤q1, the data analysis unit determines that the light intensity is normal, and sets the light abnormality coefficient to GY1, setting GY1=0; if q0>q1, the data analysis unit determines that the light intensity is abnormal, and sets the light abnormality coefficient to GY2, setting GY2=(q0-q1) / q0; the data analysis unit helps identify environmental factors that may affect the user's physiological and mental health by monitoring the abnormalities of environmental noise and light intensity, thereby improving the accuracy of environmental status analysis.

[0035] Specifically, the environmental noise and light intensity collected during the monitoring period in this embodiment are average values ​​collected during the monitoring period.

[0036] It can be understood that the present embodiment does not specifically limit the setting of the preset noise and the preset light intensity, and those skilled in the art can freely set them as long as the setting requirements of the preset noise and the preset light intensity are met, wherein the optimal value of z1 is 60dB, and the optimal value of q1 is 300Lux.

[0037] Please continue reading Figure 3 As shown, the environmental analysis module includes: An environmental analysis unit connected to the data analysis unit, the environmental analysis unit is used to analyze the environmental state index HT according to the analysis results of the environmental noise abnormality and the light intensity abnormality during the monitoring period, and set HT=w1×noise abnormality coefficient+w2×light abnormality coefficient; the environmental analysis unit quantifies the degree of environmental abnormality by analyzing the environmental state index; The environment analysis unit analyzes the environment state according to the environment state index HT and the preset environment state threshold ht. If HT≤ht, the environment analysis unit determines that the environment state of the current monitoring period is normal. Otherwise, the environment analysis unit determines that the environment state of the current monitoring period is abnormal. The environment analysis unit calculates the environment state index HT to comprehensively evaluate the abnormal state of the environmental pressure faced by the user, thereby improving the accuracy of the environment state analysis. The environment analysis unit processes the analysis process of the user's physiological characteristics when the environment state is abnormal, sets the preset physiological state threshold after processing as st1, and sets st1=st×ln[e+α×(HT-ht)+1]; the environment analysis unit adjusts the physiological threshold to adapt to environmental changes, thereby improving the accuracy of the user's physiological characteristics analysis, thereby improving the control efficiency of the device; Among them, w1 is the noise weight, w2 is the illumination weight, w1+w2=1, and α is the preset state adjustment ratio.

[0038] It can be understood that in this embodiment, there is no specific limitation on the setting of the preset state adjustment ratio, the preset environmental state threshold and each weight. Those skilled in the art can set them freely as long as the setting requirements of the preset state adjustment ratio, the preset environmental state threshold and each weight are met. Among them, the optimal value of w1 is 0.65, the optimal value of w2 is 0.35, the optimal value of α is 0.15, and the optimal value of ht is 0.23.

[0039] Please continue reading Figure 1 As shown, the system also includes: A control module is connected to the behavior analysis module, the physiological characteristic analysis module and the environment analysis module. The control module is used to control the stimulation intensity of the device in the next monitoring cycle according to the analysis results of the abnormal behavior characteristics, the user's physiological characteristics and the environmental status during the monitoring cycle, and to process the control process according to the device pulse width and the electrode surface area.

[0040] See also Figure 4 As shown, the control module includes: The control unit is used to control the stimulation intensity of the device in the next monitoring period according to the analysis results of the abnormal behavior characteristics, the user's physiological characteristics and the environmental status during the monitoring period, wherein: When the environmental state is normal, if TX-user physiological characteristics ≤ u0, the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F1, and sets F1=f0; if TX-user physiological characteristics>u0, the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F2, and sets F2=f0+f1×η×(TX-user physiological characteristics-u0); When the environmental state is abnormal, if TX-user physiological characteristics ≤u0 / exp[-(HT-ht)], the control unit controls the stimulation intensity of the device in the next monitoring period to be F3, and sets F3=f0; if TX+user physiological characteristics>u0 / exp[-(HT-ht)], the control unit controls the stimulation intensity of the device in the next monitoring period to be F4, and sets F4=f0+f1×η×(TX-user physiological characteristics-u0); the control unit intelligently adjusts the stimulation intensity according to the abnormal characteristics of user behavior, the physiological characteristics of the user and the environmental state, so that the stimulation process is more targeted and effective, and by combining the environmental and physiological analysis results with the control strategy, real-time feedback and adjustment are achieved to ensure that the user is stimulated in the best state; Wherein, f0 is the device stimulation intensity of the current monitoring cycle, f1 is the preset intensity adjustment threshold, u0 is the preset reference threshold, η is the preset adjustment proportional coefficient, and if the control result of the device stimulation intensity in the next monitoring cycle is greater than FD, the value is FD, and FD is the preset intensity threshold.

[0041] It can be understood that, in this embodiment, there is no specific limitation on the setting of the preset intensity adjustment threshold, the preset reference threshold and the preset intensity threshold, and those skilled in the art can set them freely, as long as the setting requirements of the preset intensity adjustment threshold, the preset reference threshold and the preset intensity threshold are met, among which, the optimal value of f1 is 1mA, the optimal value of u0 is 0.2, the optimal value of η is 0.36, and the optimal value of FD is 5mA.

[0042] Please continue reading Figure 4 As shown, the control module also includes: A pulse analysis unit connected to the control unit, wherein the pulse analysis unit analyzes the pulse state of the device according to the device pulse width m0 and the preset width m1. If m0≤m1, the pulse analysis unit determines that the pulse state of the device is normal; otherwise, the pulse analysis unit determines that the pulse state of the device is abnormal; The pulse analysis unit processes the control process of the stimulation intensity of the device when the pulse state of the device is abnormal, sets the preset adjustment threshold after processing to f2, and sets f2=f1×{1-[e (m0-m1) / m1 -1] / (e-1)}, where e is the natural logarithm; the pulse analysis unit ensures the stability and effectiveness of the stimulation output by monitoring the pulse state of the device, and can adjust the stimulation intensity under abnormal conditions, optimize the stimulation effect according to actual conditions, and ensure the safety and comfort of the treatment.

[0043] It is understandable that the setting of the preset width is not specifically limited in this embodiment, and those skilled in the art can freely set it as long as the setting requirements of the preset width are met, wherein the optimal value of m1 is 350µs.

[0044] Please continue reading Figure 4 As shown, the control module also includes: An electrode analysis unit connected to the pulse analysis unit, wherein the electrode analysis unit analyzes the abnormality of the electrode surface area according to the electrode surface area j0 and the preset surface area j1. If j0≤j1, the electrode analysis unit determines that the electrode surface area is normal. Otherwise, the electrode analysis unit determines that the electrode surface area is abnormal. The electrode analysis unit processes the analysis process of the device pulse state when the electrode surface area is abnormal, adjusts the preset width after processing to m1', and sets m1'=m1×{1+[(j0-j1) / (j0+j1)] 2 The electrode analysis unit detects the surface area of ​​the electrode to ensure the effectiveness and accuracy of the stimulation, and automatically adjusts according to the electrode status to meet the changing needs of the user and improve the adaptability and use effect of the device.

[0045] It can be understood that the setting of the preset surface area is not specifically limited in this embodiment, and those skilled in the art can freely set it as long as the setting requirements of the preset surface area are met, wherein the optimal value of j1 is 1.5 cm².

[0046] Please continue reading Figure 1 As shown, the system also includes: The output module is connected to the control module, and the control module is used to output the control result of the stimulation intensity of the device in the next monitoring cycle to the user.

[0047] Specifically, the system described in this embodiment is applied to the control of the vagus nerve device. By acquiring information such as the user's heart rate, RR interval, blood oxygen saturation, skin conductivity, environmental noise and light intensity, it analyzes the abnormality and volatility of the user's heart rate, monitors the user's physiological state, and intelligently adjusts the stimulation intensity of the device based on the above analysis results, thereby improving the control efficiency of the device.

[0048] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the embodiments here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. An intelligent control system for a wearable neural stimulation device, characterized in that: include: Data collection module, used to collect user heart rate data, user physiological data, environmental data and device data; A heart rate characteristic analysis module is used to construct a heart rate abnormality index based on the user's heart rate collected during the monitoring period; Behavior analysis module, used to analyze abnormal characteristics of user behavior based on abnormal heart rate index and collected RR interval; A physiological characteristic analysis module is used to analyze the abnormality of the user's conductivity and the abnormality of the user's blood oxygen saturation according to the user's skin conductivity and the user's blood oxygen saturation collected during the monitoring period, and analyze the user's physiological characteristics according to the analysis results; The environment analysis module is used to analyze the environment status according to the environmental noise and light intensity collected during the monitoring period, and to process the analysis process of the user's physiological characteristics according to the analysis results; A control module, which is used to control the stimulation intensity of the device in the next monitoring cycle according to the analysis results of the abnormal behavior characteristics, the user's physiological characteristics and the environmental status during the monitoring cycle, and to process the control process according to the device pulse width and the electrode surface area; The output module is used to output the control result of the stimulation intensity of the device in the next monitoring cycle to the user.

2. The wearable neural stimulation device intelligent control system according to claim 1, characterized in that: The heart rate characteristic analysis module is used to analyze the abnormality of the user's heart rate according to the user's heart rate a0 collected during the monitoring period and the preset heart rate threshold a1, the user's heart rate abnormality includes normal and abnormal, and construct a heart rate abnormality index XP according to the analysis result.

3. The wearable neural stimulation device intelligent control system according to claim 2, characterized in that: The behavior analysis module is used to construct a heart rate fluctuation index according to the user's RR interval collected during the monitoring period to obtain a heart rate fluctuation coefficient B, and to construct the heart rate fluctuation index according to the heart rate fluctuation coefficient B and a preset fluctuation coefficient b; The behavior analysis module analyzes the abnormal behavior characteristics of the user according to the heart rate abnormality index XP and the heart rate fluctuation index to obtain the abnormal behavior characteristics TX of the user.

4. The wearable neural stimulation device intelligent control system according to claim 3, characterized in that: The physiological characteristic analysis module includes a physiological state analysis unit, which is used to analyze the abnormality of the user's skin conductivity according to the user's skin conductivity d0 and the preset conductivity d1 collected during the monitoring period, and the abnormality of the user's skin conductivity includes normal and abnormal; The physiological state analysis unit is also used to analyze the abnormality of the user's blood oxygen saturation based on the user's blood oxygen saturation h0 collected during monitoring and the preset saturation h1. The abnormality of the user's blood oxygen saturation includes normal and abnormal.

5. The wearable neural stimulation device intelligent control system according to claim 4, characterized in that: The physiological characteristic analysis module also includes a physiological characteristic analysis unit, which analyzes the user's physiological state coefficient ST according to the analysis results of the user's conductivity abnormality and the user's blood oxygen saturation abnormality during the monitoring period, and analyzes the user's physiological state during the monitoring period according to the user's physiological state coefficient ST and a preset physiological state threshold value st0. The user's physiological state includes normal and abnormal. If the user's physiological state in the current monitoring period is normal, the user's physiological characteristic is set to SZ1; if the user's physiological state in the current monitoring period is abnormal, the user's physiological characteristic is set to SZ2.

6. The wearable neural stimulation device intelligent control system according to claim 5, characterized in that: The environmental analysis module includes a data analysis unit, which is used to analyze the abnormality of environmental noise according to the environmental noise z0 and the preset noise z1 collected during the monitoring period. The abnormality of environmental noise includes normal and abnormal. If the environmental noise is normal, the noise abnormality coefficient is set to ZY1; if the environmental noise is abnormal, the noise abnormality coefficient is set to ZY2; The data analysis unit is also used to analyze the abnormality of the light intensity according to the light intensity q0 collected during the monitoring period and the preset light intensity q1. The abnormality of the light intensity includes normal and abnormal. If the light intensity is normal, the abnormality coefficient of the light is set to GY1; If the light intensity is abnormal, the abnormal light coefficient is set to GY2.

7. The wearable neural stimulation device intelligent control system according to claim 6, characterized in that: The environment analysis module includes an environment analysis unit, which is used to analyze the environment state index HT according to the analysis results of the abnormality of the environment noise and the abnormality of the light intensity during the monitoring period, and analyze the environment state according to the environment state index HT and the preset environment state threshold ht, and the environment state includes normal and abnormal; The environment analysis unit processes the analysis process of the user's physiological characteristics when the environment state is abnormal, and sets the processed preset physiological state threshold value as st1.

8. The wearable neural stimulation device intelligent control system according to claim 7, characterized in that: The control module includes a control unit, which is used to control the stimulation intensity of the device in the next monitoring cycle according to the analysis results of the abnormal behavior characteristics, the user's physiological characteristics and the environmental status in the monitoring cycle, wherein: When the environmental state is normal, if TX-user physiological characteristics ≤ u0, the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F1; if TX-user physiological characteristics> u0, the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F2; When the environmental state is abnormal, if TX-user physiological characteristics ≤u0 / exp[-(HT-ht)], the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F3; if TX+user physiological characteristics>u0 / exp[-(HT-ht)], the control unit controls the stimulation intensity of the device in the next monitoring cycle to be F4; Among them, u0 is the preset reference threshold.

9. The wearable neural stimulation device intelligent control system according to claim 8, characterized in that: The control module further includes a pulse analysis unit, which analyzes the pulse state of the device according to the device pulse width m0 and the preset width m1, and the device pulse state includes a normal state and an abnormal state; The pulse analysis unit processes the control process of the stimulation intensity of the device when the pulse state of the device is in an abnormal state, and sets the preset adjustment threshold after processing to f2.

10. The wearable neural stimulation device intelligent control system according to claim 9, characterized in that: The control module further includes an electrode analysis unit, which analyzes the abnormality of the electrode surface area according to the electrode surface area j0 and the preset surface area j1, and the abnormality of the electrode surface area includes normal and abnormal; The electrode analysis unit processes the analysis process of the device pulse state when the electrode surface area is abnormal, and adjusts the processed preset width to m1'.

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