Wearing device for monitoring and adjusting vegetative nerves and working principle thereof

Abstract

The invention discloses a wearing device for monitoring and adjusting vegetative nerves and a working principle thereof, the wearing device comprises a multi-mode monitoring module, a multi-mode adjusting module, an intelligent control module and a power supply module which are integrated in a wearing main body, and all the modules are electrically connected through an FPC flexible circuit board to form a cooperative working unit; the multi-mode monitoring module at least integrates an electrocardio sensor and a galvanic skin reaction sensor and is used for synchronously collecting two or more vegetative nerve associated physiological signals and transmitting the signals to the intelligent control module. The intelligent control module is internally provided with a vegetative nerve state evaluation model and is used for carrying out real-time analysis processing on the physiological signals to obtain a quantified vegetative nerve function state evaluation result, dynamically generating adaptive adjustment parameters based on the evaluation result and sending the adaptive adjustment parameters to the multi-mode adjustment module; and the multi-modal regulation module at least integrates a transcutaneous electrical nerve stimulation unit and a temperature sensing regulation unit, and is used for outputting two or more regulation signals with a synergistic effect based on the regulation parameters and performing targeted intervention on the vegetative nerve function.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of biomedical engineering and smart wearable devices, specifically relating to a wearable device for monitoring and regulating the autonomic nervous system and its control method. Background Technology

[0002] The vegetative nervous system, as the core of the human autonomic nervous system, is responsible for regulating key physiological functions such as the operation of internal organs, cardiovascular contraction, glandular secretion, and metabolic balance. The dynamic balance between the sympathetic and parasympathetic nervous systems is a crucial foundation for maintaining homeostasis. Clinical data shows that long-term irregular work and rest schedules and excessive mental stress can easily lead to vegetative nervous system dysfunction, subsequently inducing a series of psychosomatic problems such as insomnia, anxiety, hypertension, and gastrointestinal dysfunction, seriously affecting the quality of life. Current technical solutions in the field of vegetative nervous system intervention can be divided into two main directions: monitoring and regulation. Both generally suffer from core bottlenecks such as a disconnect between hardware and software design and a lack of synergy. Specifically, these shortcomings can be broken down into three points: First, monitoring devices are functionally limited. Existing devices can only collect a single signal of heart rate variability (HRV), failing to simultaneously capture multi-dimensional physiological indicators strongly correlated with vegetative nervous system activity, such as skin conductance response and respiratory rate. This leads to a one-sided assessment of the nervous system's functional state and is prone to regulatory bias due to signal misinterpretation. Second, regulation device parameters are fixed. Regulation methods such as electrical stimulation, magnetic therapy, and temperature sensing are mostly based on preset programs. The output signals have fixed strength and frequency, lacking dynamic linkage with real-time monitoring data. This makes it impossible to adapt to the differences in physical condition and degree of neurological disorders among different individuals. Not only is the regulation accuracy low and the effect unstable, but improper parameters may also cause nerve stimulation or secondary damage to sensitive individuals. Thirdly, there is a lack of software and hardware co-design. In the existing solutions, the monitoring module and the regulation module are mostly independent components. The regulation principle is not adapted to the acquisition capability of the monitoring hardware, and the monitoring data cannot be efficiently converted into regulation commands, forming a technical barrier of "disconnect between monitoring and regulation". It is difficult to achieve precise and dynamic closed-loop control of vegetative-neural intervention.

[0003] For example, the invention patent with publication number CN114522341A, whose actual title is "Device, System and Method for Stimulation Therapy," provides a treatment plan based on electrical stimulation, specifically including a stimulation module, a control module, and a wearable component. It achieves intervention by outputting electrical stimulation signals to specific nerve distribution areas in the human body. However, this device has significant limitations in vegetative-neural intervention scenarios: First, its functional design is singular, focusing only on electrical stimulation regulation without integrating a vegetative-neural state monitoring module, thus failing to acquire real-time physiological signals from the user; second, parameter control is fixed, requiring pre-setting and writing of parameters such as voltage and frequency into the control program, making it unable to adaptively adjust based on dynamic changes in the vegetative-neural system; third, the intervention logic is one-sided, failing to design a synergistic regulation strategy to address the balance needs of the sympathetic-parasympathetic dual systems of the vegetative-neural system, and can only output electrical stimulation of a single intensity, resulting in poor adaptability and insufficient regulation precision, making it difficult to meet the personalized and precise intervention needs of users with different degrees of disorder and different physical conditions.

[0004] For example, the invention patent with publication number CN111632266B is entitled "A Brain Function Regulation and Treatment System". The core of this system is used for brain cognitive training. It consists of a superimposed current stimulation helmet, a mobile contact current stimulator, a controller and a computer. It outputs superimposed current through multiple sets of current stimulators to act on specific areas of the brain. It can avoid the side effects of excessive current from a single current while realizing current monitoring and protection, stimulation position adjustment and training program customization. However, this system differs fundamentally from the needs of vegetative-neural intervention and cannot be adapted to vegetative-neural regulation scenarios: First, it suffers from targeting bias, regulating the overall brain function without designing specific monitoring programs for vegetative-neural specific physiological indicators (such as skin conductance response, the synergistic relationship between respiratory rate and heart rate variability). It can only indirectly feed back brain responses through electrodes, failing to accurately quantify the functional state of the vegetative-neural system. Second, it employs a single regulation method, relying solely on electrical stimulation without auxiliary regulation units such as temperature sensing or magnetic therapy, making it difficult to adapt to the complex pathological mechanisms of vegetative-neural disorders. Third, it lacks closed-loop logic. Although it possesses a basic framework of "collection-assessment-regulation," its core is based on customizing fixed training programs based on historical stimulation data, rather than dynamic closed-loop regulation driven by real-time physiological signals. The regulation parameters are not directly linked to the real-time state of the vegetative-neural system, resulting in poor monitoring and regulation adaptability and insufficient intervention targeting, making it unable to cope with complex vegetative-neural disorder conditions. The two patents mentioned above represent the mainstream directions of "single regulation" and "specific regulation of brain function" in the field of neurointervention, respectively. Neither of them has broken through the core bottlenecks of "disconnect between monitoring and regulation, lack of hardware and software synergy, and insufficient targeting of the autonomic nervous system," and cannot meet the needs of clinical adjuvant therapy and daily health management for precise intervention of the autonomic nervous system.

[0005] Further analysis of the technical architecture reveals that the shortcomings of the two patents essentially point to common weaknesses in existing technologies. While the invention patent with publication number CN111632266B achieves adjustable electrical stimulation parameters and current safety protection, its helmet-style hardware architecture, designed specifically for brain stimulation, is not only cumbersome to wear and unsuitable for extended periods, but also lacks internal space for integrating a multimodal monitoring module, thus limiting its compatibility with vegetative-neural monitoring functions from the hardware level. In terms of software logic, its evaluation module assesses treatment effectiveness solely based on current feedback and historical training data, lacking a dedicated quantitative model for vegetative-neural functions, thus failing to provide data support for precise intervention. The invention patent with publication number CN114522341A, with its single stimulation architecture, lacks a collaborative design with monitoring functions and has no real-time signal feedback link, essentially operating on a "blind adjustment" model, unable to avoid intervention biases caused by inappropriate parameters. Both issues expose the core problem of existing technologies: they fail to construct a hardware and software collaborative system that integrates "multimodal dedicated monitoring, quantitative assessment, multi-dimensional collaborative regulation, and real-time closed-loop feedback" to address the physiological characteristics and regulatory needs of the vegetative nervous system. Either they only focus on regulatory functions and lack precise monitoring support, or they target specific brain function regulation but cannot adapt to the needs of the vegetative nervous system. There is an urgent need for a wearable solution that targets the vegetative nervous system and deeply integrates hardware and software to overcome the application limitations of existing technologies.

[0006] It should be noted that the above technical information is the result of the inventor's creative labor. The detailed description of the technology in the background section is only intended to deepen the understanding of the overall background technology of the invention, and should not be regarded as an admission or in any form an implication that the above technical information constitutes prior art known to those skilled in the art. Summary of the Invention

[0007] To address the shortcomings in the aforementioned background technology, this invention proposes a wearable device and its control method for monitoring and regulating the vegetative nervous system. The technical problem to be solved is that existing vegetative nervous system intervention devices are disconnected from the regulation principle, have poor hardware and software synergy, and suffer from problems such as single monitoring dimensions, fixed regulation parameters, insufficient targeting, and discomfort when worn. This results in insufficient linkage between monitoring and regulation, parameters that cannot dynamically adapt to the individual's real-time state, low regulation accuracy, unstable effects, and limited applicable scenarios.

[0008] The technical solution of this invention is as follows:

[0009] A wearable device for monitoring and regulating the vegetative nervous system includes a body adapted to the head, neck, chest, and back. The wearable body integrates a multimodal monitoring module, a multimodal regulation module, an intelligent control module, and a power supply module. These modules are electrically connected via a flexible printed circuit board (FPC) to form a collaborative working unit. The multimodal monitoring module integrates at least an electrocardiogram (ECG) sensor and a transcutaneous electrical response (TEG) sensor to simultaneously collect two or more physiological signals associated with the vegetative nervous system and transmit them to the intelligent control module. The intelligent control module incorporates a vegetative nervous system state assessment model to perform real-time analysis and processing of the physiological signals, obtaining a quantified assessment result of the vegetative nervous system function state. Based on the assessment result, it dynamically generates appropriate regulation parameters and sends them to the multimodal regulation module. The multimodal regulation module integrates at least a transcutaneous electrical nerve stimulation (TENS) unit and a thermosensitive regulation unit to output two or more synergistic regulatory signals based on the regulation parameters, targeting and intervening in vegetative nervous system function.

[0010] The beneficial effects of this technical solution are as follows:

[0011] Firstly, it addresses the challenge of insufficient hardware coordination in existing technologies by constructing an integrated architecture. By integrating multimodal monitoring, adjustment, intelligent control, and power supply modules into a wearable body that fits the head and neck area, and relying on FPC flexible circuit boards to achieve electrical connections between the modules, it solves the shortcomings of existing devices, such as single stimulation modules lacking monitoring functions, cumbersome helmet-style architecture, and inability to integrate multimodal modules. This achieves hardware miniaturization and portability, while ensuring the stability of the coordinated operation of each module, providing a dedicated hardware carrier for the subsequent implementation of the principle.

[0012] Secondly, it breaks through the bottleneck of single monitoring and regulation, laying the foundation for precise intervention. The multimodal monitoring module simultaneously collects ECG and skin conductance signals, making up for the one-sidedness of assessment by only collecting a single signal in existing equipment, and ensuring the integrity of vegetative nervous system state data; the multimodal regulation module integrates electrical stimulation and temperature sensing units, avoiding the problem of poor adaptability of single regulation methods, and can output synergistic signals for the balance needs of sympathetic-parasympathetic nerves, improving the targeting of intervention;

[0013] Third, it strengthens the hardware's support capabilities for signal processing and parameter output. The intelligent control module has a built-in dedicated evaluation model that can convert monitoring data into quantitative results in real time and generate appropriate adjustment parameters, avoiding the disconnect between hardware and algorithms. This solves the problems of fixed parameters and lack of dedicated autonomic nervous system evaluation logic in existing technologies, providing hardware computing power support for dynamic intervention.

[0014] Based on the above technical solutions, as a preferred technical solution for the wearable device used to monitor and regulate the autonomic nervous system, the multimodal monitoring module further includes a respiratory rate sensor integrated into the wearer's body at the corresponding chest position, with a measurement range of 10-60 breaths / minute and an error of ±0.5 breaths / minute; an electrocardiogram sensor attached to the carotid artery, with a sampling rate of 250-500Hz and an accuracy of ±0.01mV; and a skin conductance sensor attached to the skin behind the ear, with a measurement range of 0-50μS and a resolution of 0.01μS.

[0015] Further beneficial effects of this technical solution are: by using three sensors to collect data collaboratively, it provides multi-dimensional data support for the quantitative evaluation in the principle, further improves the accuracy of the evaluation results, avoids adjustment deviations caused by misjudgment of a single signal, and enhances the reliability of software and hardware collaboration.

[0016] Based on the above technical solution, as a preferred technical solution for the wearable device for monitoring and regulating the vegetative nervous system, the multimodal adjustment module further includes a low-frequency pulse magnetic therapy unit with a magnetic field strength adjustment range of 0.05-0.5T and a frequency of 0.5-50Hz, which works in conjunction with the transcutaneous electrical nerve stimulation unit and the temperature sensing adjustment unit; the transcutaneous electrical nerve stimulation unit outputs a voltage range of 0.1-5V and a frequency of 1-100Hz; the temperature sensing adjustment unit adjusts the temperature range of 32-40℃ with an accuracy of ±0.1℃.

[0017] Further beneficial effects of this technical solution are: enriching the regulatory dimensions, making the synergistic intervention in the principle more targeted, adaptable to different disorder types such as sympathetic nerve excitation and parasympathetic nerve inhibition, expanding the applicable scenarios of the principle based on the device hardware, and improving the universality of synergistic intervention.

[0018] Based on the above technical solutions, as a preferred technical solution for the wearable device for monitoring and regulating the autonomic nervous system, the evaluation model of the intelligent control module is constructed based on the random forest algorithm, inputting ECG, skin conductance, and respiratory rate characteristic parameters, and outputting the ratio of sympathetic and parasympathetic nerve activity; a built-in parameter matching algorithm is used to call a preset individual adaptation parameter library based on the evaluation results, dynamically adjusting the output parameters of the multimodal regulation module, with a data processing delay of ≤1s.

[0019] Further beneficial effects of this technical solution are: algorithm optimization enables the device to respond quickly to changes in physiological signals, providing speed support for the closed-loop feedback in the principle, ensuring the real-time adjustment of adjustment parameters, and enhancing the dynamic response capability of software and hardware collaboration.

[0020] Based on the above technical solutions, as a preferred technical solution for the wearable device for monitoring and regulating the vegetative nervous system, the main body of the wearer is made of flexible silicone material with a Shore hardness of 30-40, with a built-in memory metal bracket, an overall weight of ≤80g, ventilation holes with a diameter of 0.5-1mm set in the contact area, and adjustable straps with an adjustment range of 30-45cm set on both sides.

[0021] Further benefits of this technical solution include: optimizing wearing comfort, ensuring stable wear of the device for extended periods, providing continuous hardware support for the closed-loop monitoring and adjustment throughout the entire process, and preventing interruptions to the collaborative workflow due to dislodging or discomfort.

[0022] Based on the above technical solutions, as a preferred technical solution for the wearable device for monitoring and regulating the vegetative nerve, the electrodes of the transcutaneous electrical nerve stimulation unit are made of medical-grade silver chloride material, with an electrode area of ​​1-2 cm², and coated with a conductive gel of 0.1-0.2 mm thickness at the skin contact point.

[0023] Further beneficial effects of this technical solution are: improving the biocompatibility and signal transmission stability of the electrodes and skin, ensuring that the regulation signal output by the device accurately acts on the target nerve, ensuring the consistency of the effect of synergistic intervention in the principle, and reducing the impact of hardware contact problems on the implementation of the principle.

[0024] Based on the above technical solutions, the preferred technical solution for the wearable device for monitoring and regulating the vegetative nervous system also includes an interactive module, which integrates an OLED display screen and buttons. The display screen is used to display the vegetative nervous system status assessment results, adjustment parameters, and battery level in real time, and the buttons are used to switch working modes and start / stop adjustment functions.

[0025] Further benefits of this technical solution include: enabling human-computer interaction, allowing users to intuitively grasp the collaborative working status of software and hardware, and enabling manual intervention and adjustment of the process, making the implementation of the principle more flexible and adaptable to different usage scenarios.

[0026] Based on the above technical solution, as a preferred technical solution for the wearable device for monitoring and regulating the autonomic nervous system, the intelligent control module also has a built-in safety protection unit. When an abnormal physiological signal with a heart rate >120 beats / minute or <50 beats / minute is detected, or when the output parameters of the regulation module exceed the safety threshold, the regulation function is immediately stopped and an audible and visual alarm is issued.

[0027] The further beneficial effects of this technical solution are: it provides a safety net for the collaborative work of software and hardware, avoids health risks caused by abnormal parameters or sudden individual conditions during the implementation of the principle, and improves the safety of the collaborative work of the device and the principle.

[0028] The working principle of a wearable device for monitoring and regulating the autonomic nervous system, employing any of the aforementioned technical solutions, relies on a multimodal hardware and software collaborative architecture to achieve full-process linkage of "signal acquisition - quantitative evaluation - dynamic adjustment - closed-loop feedback," specifically including the following core steps:

[0029] 1) The multimodal monitoring module simultaneously collects human electrocardiogram and skin conductance signals, which are then filtered, amplified, and preprocessed before being transmitted to the intelligent control module;

[0030] 2) The intelligent control module extracts signal feature parameters through the evaluation model, calculates the ratio of sympathetic to parasympathetic nerve activity, and quantitatively evaluates the functional status of the autonomic nervous system.

[0031] 3) Based on the evaluation results, dynamically generate adaptive adjustment parameters, control the output of the multimodal adjustment module to coordinate adjustment signals, and target intervention in neural function;

[0032] 4) Continuously collect physiological signals during the regulation process and feed them back to the intelligent control module in real time to dynamically adjust the regulation parameters and form a closed-loop control.

[0033] The beneficial effects of this technical solution are as follows:

[0034] First, it constructs a closed-loop logic for the entire process to solve the pain point of the disconnect between monitoring and regulation. Relying on the device's multimodal hardware and software architecture, it builds a "signal acquisition-quantitative evaluation-dynamic regulation-closed-loop feedback" link, breaking through the limitations of existing technologies that rely on fixed stimuli without real-time feedback and customized solutions based on historical data. This enables real-time linkage between monitoring data and regulation commands, allowing intervention to shift from "blind" to "precise".

[0035] Secondly, quantitative assessment improves the accuracy of neural state determination. By extracting signal feature parameters and calculating the sympathetic-parasympathetic nerve activity ratio, the functional state of the plant nervous system is transformed from a qualitative description to a quantitative assessment, avoiding the ambiguity problem of traditional assessments, providing a scientific basis for the generation of dynamic regulation parameters, and making up for the shortcomings of existing technologies in accurately quantifying the state of the plant nervous system.

[0036] Third, it achieves personalized dynamic adaptation and enhances the stability of intervention effects. Based on the evaluation results, the adjustment parameters are dynamically generated, and the parameters are optimized by continuously collecting physiological signals during the adjustment process. This can adapt to the differences in physical condition and degree of neurological disorder among different individuals, solving the problems of fixed adjustment parameters and poor adaptability in existing technologies. At the same time, it maximizes the performance advantages of the device's multimodal hardware, allowing the hardware components to form an organic linkage through principle logic, rather than independent operating units.

[0037] Fourth, the hardware architecture of the aforementioned device-type technical solutions provides dedicated support for the closed-loop process of this technical solution. The hardware design with multiple sensors and multiple adjustment units ensures that the quantitative evaluation and collaborative intervention in the principle can be implemented. The process design of the principle-type claims activates the hardware performance of the device and avoids the hardware modules from falling into the limitation of "fighting alone". The two work together to accurately solve the core defects of "blind adjustment" and "targeting deviation" in the existing technology. Compared with single hardware improvement or single principle optimization, the improvement in adjustment effect brought about by the synergistic effect has significant non-obviousness.

[0038] Based on the above technical solution, as a preferred technical solution for the working principle of the wearable device for monitoring and regulating the autonomic nervous system, in step 2, the normal range of the ratio of sympathetic nerve activity to parasympathetic nerve activity is set to 1.2-1.8. When the ratio is >1.8, the transcutaneous electrostimulation unit outputs a low-frequency signal of 1-10Hz and the temperature-sensing adjustment unit maintains a constant temperature of 37-38℃ to synergistically inhibit sympathetic nerve activity; when the ratio is <1.2, the transcutaneous electrostimulation unit outputs a high-frequency signal of 50-100Hz and the temperature-sensing adjustment unit maintains a constant temperature of 35-36℃ to synergistically activate the parasympathetic nervous system.

[0039] The further beneficial effects of this technical solution are as follows:

[0040] Step 2 further clarifies the judgment criteria and parameter matching logic of quantitative adjustment in the principle, and accurately adapts to the hardware of the multimodal adjustment module of the device, making the software and hardware collaboration more targeted and improving the stability of the adjustment effect.

[0041] In step 4, the physiological signal acquisition and evaluation results are updated every 1 second, and the regulation parameters are adjusted synchronously to form a high-frequency closed-loop feedback. If three consecutive evaluation results are within the normal range, the regulation signal intensity is automatically reduced to the baseline maintenance level. Beneficial effects: The optimized closed-loop control rhythm is adapted to the rapid processing capabilities of the device's intelligent control module, reducing unnecessary signal stimulation while ensuring the regulation effect, further enhancing the accuracy and comfort of hardware and software collaboration.

[0042] This invention, through deep collaborative innovation in device hardware architecture and working principle, precisely targets the core defects in the background technology, breaking through the triple bottlenecks of existing technologies: "disconnect between monitoring and regulation, fragmented software and hardware design, and insufficient targeting of the plant nervous system." It constructs a complete technical system of "plant nervous system-specific multimodal monitoring - quantitative assessment - multi-dimensional collaborative regulation - high-frequency closed-loop feedback," achieving a leapfrog improvement in plant nervous system intervention from "non-targeted and immobilized" to "precise, personalized, and long-lasting." Its overall beneficial effects can be specifically manifested in three dimensions: collaborative creativity, functional targeting, and practical adaptability.

[0043] Firstly, the synergistic integration of hardware and software enables a creative breakthrough, precisely filling gaps in existing technologies. Compared to the limitations of existing technologies that rely on "single electrical stimulation without real-time monitoring," the multimodal monitoring module (ECG + skin conductance + respiration) and the multimodal regulation module (electrical stimulation + temperature sensing + magnetic therapy) of this invention form a hardware complementarity. Combined with the vegetative-neural-specific assessment model (based on the random forest algorithm) of the intelligent control module, a closed-loop architecture of "monitoring-assessment-regulation-feedback" is constructed, allowing the regulation parameters to be dynamically adjusted in real time according to the vegetative-neural state, completely eliminating the blindness of fixed parameters. Compared to the limitations of existing technologies that are "brain-targeted, single electrical stimulation, and non-real-time closed-loop," the hardware of this invention adopts a U-shaped flexible wearable design, which is adapted to the densely populated vegetative-neural areas of the head and neck. The exclusive monitoring indicators and quantitative models accurately target the assessment of vegetative-neural function, and the multi-dimensional regulation unit adapts to the sympathetic-parasympathetic balance needs. Moreover, the 1-second high-frequency closed-loop feedback logic far exceeds the historical data-driven mode of existing technologies. This hardware and software co-design makes the device and principle form an organic whole. Compared with the two existing technical solutions, the improvement in intervention targeting, real-time performance and accuracy is significant and non-obvious, and fully meets the patent inventiveness requirements.

[0044] Secondly, the device features targeted optimization, balancing intervention effectiveness with safety and comfort. In terms of targeting, the device's multimodal monitoring module focuses on autonomic nervous system-specific indicators (heart rate variability, skin conductance response, respiratory rate), and the evaluation model specifically calculates the sympathetic-parasympathetic nerve activity ratio (normal range 1.2-1.8). Compared to existing non-targeted brain modulation technologies, this significantly improves the targeted intervention for autonomic nervous system disorders. Regarding regulatory effects, the multi-dimensional synergistic regulation unit can dynamically combine intervention methods according to the type of nervous system disorder. Compared to the single electrical stimulation of existing technologies, this avoids tolerance issues caused by single stimulation, resulting in more stable intervention effects. In terms of safety, intelligent control… The safety protection unit of the control module can monitor abnormal heart rate and trigger alarms when adjustment parameters exceed limits. This not only makes up for the lack of safety monitoring in existing technologies, but also optimizes the single protection logic of existing technologies that only target current. In specific implementations, it also adds protection against poor contact and overheating, building multiple safety defenses. In terms of comfort, the flexible silicone U-shaped wearing body, combined with the principle of "maintaining intensity after reaching the standard", solves the problems of the cumbersome wearing and unsuitability for long-term use of the helmet-style design in existing technologies. It can support more than 8 hours of continuous intervention (corresponding to the battery life and wearing design of the specific implementation method), ensuring the long-term effectiveness of the intervention.

[0045] Thirdly, its practical adaptability is expanded, covering multiple scenarios and facilitating large-scale promotion. The device of this invention integrates an interactive module, supporting OLED screen display and button operation. It is compact, easy to operate, and can be used at home without the guidance of professional medical personnel. It also supports data synchronization to a mobile terminal APP (see specific implementation method). It can meet the needs of multiple scenarios such as daily health management, assisted treatment of vegetative-nervous system disorders, and postoperative rehabilitation monitoring. Compared to the limitations of existing technologies in professional medical scenarios, its universality is significantly improved. The hardware uses medical-grade environmentally friendly materials and mature sensors and chip components, making production costs controllable. Its flexible wearing design adapts to different head and neck sizes, making it easier to mass-produce compared to the dedicated devices of the two existing technologies. The operating principle can be continuously optimized and adjusted based on user historical data, adapting to special populations such as the elderly, children, and those with chronic diseases combined with neurological disorders. Furthermore, its battery life reaches 12 hours (see specific implementation method power supply module design), solving the problem of insufficient portability in existing devices. In summary, through the deep synergy between the device and the principle, this invention not only precisely compensates for the technical deficiencies of the two existing technologies, but also constructs a "precisely targeted, safe and long-lasting, easy-to-use and portable" vegetative-neural intervention solution, which has important technological leading significance and broad market application prospects in the interdisciplinary field of biomedical engineering and smart wearables. Attached Figure Description

[0046] To more clearly illustrate the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A front view (perspective) of the application status of a wearable device used to monitor and regulate the autonomic nervous system.

[0048] Figure 2 Rear view (perspective) of the wearable device used for monitoring and regulating the autonomic nervous system.

[0049] Figure 3 This is a block diagram illustrating the structure of the multimodal monitoring module, multimodal adjustment module, and intelligent control module of the present invention.

[0050] Figure 4 This is a block diagram illustrating the principle of closed-loop control in this invention.

[0051] Explanation of markings in the diagram: 1-Wearing body, 2-Multimodal monitoring module, 21-ECG sensor, 22-Electrodermal response sensor, 23-Respiratory rate sensor, 3-Multimodal adjustment module, 31-Transcutaneous electrical nerve stimulation unit, 32-Low-frequency pulse magnetic therapy unit, 33-Temperature adjustment unit, 4-Intelligent control module, 41-Evaluation model chip, 42-Parameter matching chip, 43-Safety protection unit, 5-Power supply module, 6-Interaction module, 61-OLED display screen, 62-Buttons, 7-FPC flexible circuit board, 8-Ventilation hole, 9-Adjustable strap. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the core concept of the present invention and the following embodiments, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] I. General Implementation Examples

[0054] like Figures 1 to 4 As shown, this embodiment discloses a wearable device for monitoring and regulating the autonomic nervous system, and the hardware and software collaborative working principle based on this device. The overall structure of the device is as follows. Figures 1 to 3 As shown, the collaborative workflow is as follows: Figure 4 As shown, the following details the structural features of the device, assembly relationships, parameter settings, and the collaborative working process and usage methods of the device and its principles, ensuring that the disclosure is sufficient and feasible.

[0055] (I) Structural features and assembly relationships of the device

[0056] The main body 1 has a U-shaped structure, fitting the back and sides of the neck. It is made of medical-grade flexible silicone with a Shore hardness of 35 and features a built-in 2mm diameter memory metal support that adapts to the contours of the user's head, neck, chest, and back. Weighing only 160g, it ensures a snug fit while enhancing comfort. The inner side of the main body 1 has evenly distributed ventilation holes 8 (0.8mm diameter, 2.5mm spacing) in contact with the skin. Adjustable nylon straps 9 are located on both sides and secured with Velcro, offering an adjustment range of 32-43cm to accommodate individuals with different head and neck sizes.

[0057] The wearable unit 1 integrates a multimodal monitoring module 2, a multimodal adjustment module 3, an intelligent control module 4, a power supply module 5, and an interaction module 6 via an FPC flexible circuit board 7. These modules are electrically connected to form a collaborative working unit. It should be noted that the attached diagram is for illustrative purposes only; not all FPC flexible circuit boards 7 are shown in the diagram for ease of viewing.

[0058] Multimodal monitoring module 2, such as Figure 1 and Figure 2 As shown, the ECG sensor 21 is model AD8232, which is mounted on the wearer 1 at the left carotid artery and fixed with medical double-sided tape. It has a sampling rate of 300Hz and an accuracy of ±0.01mV and is used to collect heart rate variability signals.

[0059] The skin conductance sensor 22 is model TCS3472, which is fitted behind the right ear. It has a measurement range of 0-50μS and a resolution of 0.01μS and is used to collect skin conductance change signals.

[0060] The respiratory rate sensor 23 is model SDP3X, which is integrated into the front of the wearable body 1 at the position corresponding to the chest. It collects respiratory signals through pressure sensing, with a measurement range of 10-60 breaths / minute and an error of ±0.5 breaths / minute. The three sensors work together to achieve multi-dimensional signal acquisition.

[0061] Multimodal conditioning module 3, such as Figure 1 and Figure 2 As shown, the transcutaneous electrical nerve stimulation unit 31 is mounted on the inner side of the wearer 1 at the position corresponding to the cervical sympathetic ganglion (one on each side). The electrodes are made of medical silver chloride material with an area of ​​1.5 cm². The side in contact with the skin is coated with a 0.15 mm thick conductive gel to ensure stable signal transmission.

[0062] The low-frequency pulse magnetic therapy unit 32 is model MP-100, which is integrated into the center of the back of the neck of the wearer 1. The coil diameter is 2cm and the magnetic field strength can be adjusted from 0.05 to 0.5T.

[0063] The temperature sensing adjustment unit 33 is a ceramic heating element, several of which are used. Each element is 2×1cm in size and fits the back of the neck. The adjustment range is 32-40℃ with an accuracy of ±0.1℃. The three elements work together to achieve multi-mode intervention.

[0064] The core chip of the intelligent control module 4 is STM32H743, which integrates a plant neural state assessment model chip 41 based on the random forest algorithm (training sample size ≥1000 sets of human physiological data), a parameter matching chip 42, and a safety protection unit 43. The safety protection unit 43 integrates overcurrent, overvoltage and abnormal signal detection circuits, and the data processing delay is ≤1s to ensure real-time response.

[0065] The power supply module 5 is a 500mAh lithium-ion battery (30×20×5mm), which is installed inside the right side of the wearable body 1. It supports 5W wireless charging, charging time is 1.8 hours, battery life is 12 hours, and low battery (remaining battery ≤20%) is indicated by sound and light.

[0066] The interaction module 6 is mounted on the left outer side of the wearer 1. The OLED display 61 is 1.7 inches in size with a resolution of 320×240. The buttons 62 are made of silicone (two buttons, namely the power / mode button and the start / stop button), which are used for human-computer interaction.

[0067] (ii) Device parameter setting

[0068] 1. Monitoring parameters: ECG sensor signal amplification factor 1000 times, filtering range 0.5-50Hz; skin conductance sensor sampling frequency 100Hz, filtering accuracy 0.001μS; respiratory rate sensor sampling frequency 50Hz, pressure sensing range 0-10kPa.

[0069] 2. Adjustable parameters: The output voltage of the transcutaneous electrical nerve stimulation unit is 0.1-5V, the frequency is 1-100Hz, the pulse width is 0.1-1ms, and the voltage step is adjustable by 0.1V and the frequency step is adjustable by 1Hz; the low-frequency pulse magnetic therapy unit has a frequency of 0.5-50Hz and a duty cycle of 50%; the temperature sensing adjustment unit has a heating rate of 0.5℃ / min and a constant temperature accuracy of ±0.1℃.

[0070] 3. Control and safety parameters: The error of the sympathetic / parasympathetic nerve activity ratio output by the evaluation model is ±0.05; the safety protection threshold is set as heart rate >120 beats / minute or <50 beats / minute, and skin conductance signal >40μS or <5μS. After the protection is triggered, the power supply to the regulating module will be cut off immediately and an alarm will be triggered.

[0071] (III) The process of coordinated operation of the device and the principle

[0072] The working principle of this embodiment relies on the hardware and software architecture of the above-mentioned device to achieve closed-loop coordination of "acquisition-evaluation-adjustment-feedback". The specific process is as follows:

[0073] 1. Signal Acquisition Stage: After the device is powered on and worn stably, the three sensors of the multimodal monitoring module 2 start up synchronously. The ECG sensor 21 collects the heart rate variability signal at the carotid artery, the skin conductance sensor 22 collects the skin conductance signal behind the ear, and the respiratory rate sensor 23 collects the respiratory signal corresponding to the change in chest pressure. Each signal is transmitted to the intelligent control module 4 via the FPC flexible circuit board 7. After preprocessing by the built-in filtering and amplification circuit, environmental interference and noise signals are removed to ensure signal purity and provide reliable data for subsequent evaluation. This stage relies on the synchronous acquisition capability of the device's multi-sensor hardware and is the basis for the implementation of the principle.

[0074] 2. Quantitative Evaluation Stage: The evaluation model chip 41 of the intelligent control module 4 extracts the preprocessed ECG SDNN, RMSSD index, skin conductance changes, and respiratory cycle characteristic parameters. Based on the random forest algorithm, it calculates the ratio of sympathetic to parasympathetic nerve activity. The ratio is set to 1.2-1.8 as the normal range. A ratio >1.8 is judged as sympathetic nerve excitation, and a ratio <1.2 is judged as parasympathetic nerve inhibition. The evaluation results are transmitted to the display screen of the interaction module 6 in real time. This stage relies on the algorithm chip hardware of the device to realize the quantitative evaluation logic of the principle, avoiding the ambiguity of traditional qualitative evaluation.

[0075] 3. Dynamic Adjustment Stage: Based on the evaluation results, the parameter matching chip 42 calls the built-in individual adaptation parameter library to dynamically generate adjustment instructions: When the sympathetic nervous system is excited (ratio > 1.8), the transcutaneous electrical nerve stimulation unit outputs a 1-10Hz low-frequency, 0.1-1V low-voltage signal, the low-frequency pulse magnetic therapy unit outputs a 0.05-0.1T magnetic field (frequency 0.5-5Hz), and the temperature adjustment unit maintains a constant temperature of 37-38℃. The three work together to inhibit sympathetic nerve activity. When the parasympathetic nervous system is inhibited (ratio < 1.2), the transcutaneous electrical nerve stimulation unit outputs a 50-100Hz high-frequency, 2-3V medium-voltage signal, the low-frequency pulse magnetic therapy unit outputs a 0.2-0.3T magnetic field (frequency 20-30Hz), and the temperature adjustment unit maintains a temperature of 35-36℃. This works together to activate the parasympathetic nervous system. This stage realizes the principle of coordinated adjustment logic. The device's multi-adjustment unit hardware provides a multi-dimensional intervention carrier for the principle, which is more effective than a single adjustment method.

[0076] 4. Closed-loop feedback stage: During the adjustment process, the multimodal monitoring module 2 continuously collects the user's physiological signals and transmits them to the intelligent control module 4 every 1 second to update the evaluation results. The parameter matching chip 42 synchronously adjusts the adjustment parameters to form a high-frequency closed-loop feedback. If the evaluation results are within the normal range of 1.2-1.8 for three consecutive times, the transcutaneous electrical stimulation voltage is automatically reduced by 30% and the magnetic field strength is reduced by 20% to maintain the basic adjustment level. The safety protection unit 43 synchronously monitors the physiological signals and adjustment parameters. If the safety threshold is exceeded, the power supply to the adjustment module is immediately cut off, alarm information is displayed on the OLED screen, and a 2kHz buzzer is emitted at 1 second interval. At the same time, the monitoring function is kept running to ensure user safety. This stage relies on the device's rapid processing and safety protection hardware to achieve dynamic optimization of the principle and safety backup, and enhance collaborative reliability.

[0077] (iv) Instructions for use

[0078] 1. Preparation for wearing: Clean the skin of the neck and behind the ears to remove oil and debris. Apply the conductive gel of the transcutaneous electrical nerve stimulation unit electrode 311 evenly to ensure there are no air bubbles. Place the main body 1 against the back of the neck and adjust the strap 10 to a suitable tightness (fitting against the skin without pressure). Check that each sensor is in close contact with the skin and that there is no displacement or suspension.

[0079] 2. Power-on startup: Press the power / mode button for 3 seconds to power on. The device will automatically enter monitoring mode. The OLED display 61 shows real-time ECG, skin conductance, respiratory signals and nerve activity ratio. Simultaneously, it connects to the mobile terminal APP via Bluetooth (optional data transmission module) to complete initialization.

[0080] 3. Adjustment Operation: The automatic adjustment mode is enabled by default, and the device automatically runs the closed-loop process according to the above-mentioned collaborative principle. Users can manually start and stop the adjustment function through the start / stop button, press the power / mode button to switch to manual mode, and use button 62 to switch parameter types by short press and adjust values ​​by long press to adapt to personalized needs.

[0081] 4. Data Viewing and Maintenance: The mobile terminal APP synchronously stores monitoring data and adjustment records, and generates daily and weekly trend reports. Users and medical staff can view changes in the vegetative nervous system state and the adjustment effect. After use, press the power / mode button for 5 seconds to turn off the device. When the display shows low battery, place the device on the wireless charging dock (corresponding to the charging area on the right side of the wearer 1) to charge. The device will automatically power off after charging is complete. Clean the residual gel on the electrodes and store it properly.

[0082] II. Specific Examples

[0083] Example 1

[0084] This embodiment focuses on optimizing the intelligent control module algorithm, enhancing the synergistic effect of quantitative evaluation and parameter matching in the device and its principles. The device structure is basically the same as the general embodiment, with only the parameters of the intelligent control module adjusted, as follows:

[0085] Device parameter adjustment: The evaluation model of the intelligent control module is replaced with a CNN-LSTM hybrid deep learning model, the training sample size is increased to 5000 groups, and the transfer learning function is integrated. It can adaptively optimize the evaluation model based on the user's historical data within one week; the parameter matching algorithm is replaced with a reinforcement learning algorithm, with "the ratio of neural activity tending to the normal range" as the reward goal, and autonomously explores the optimal combination of adjustment parameters without relying on a preset parameter library.

[0086] Optimized Collaborative Working Principle: While the signal acquisition and adjustment hardware remains unchanged, the evaluation phase utilizes transfer learning to fit individual user physiological characteristics. After one week of use, the evaluation error is ≤±0.02, addressing evaluation biases caused by individual differences. In the parameter matching phase, a reinforcement learning algorithm is used to autonomously optimize and adjust parameter combinations (e.g., reducing electrical stimulation voltage, increasing temperature sensitivity) for users with cardiovascular diseases, avoiding the limitations of a preset parameter library. This embodiment, through algorithm and hardware optimization, makes the quantitative evaluation of the principle more accurate, parameter matching more personalized, and significantly improves the collaborative adaptability between the device and the principle, making it suitable for users with special physical conditions or those requiring long-term use.

[0087] Example 2

[0088] This embodiment focuses on optimizing the adjustment logic of the working principle, ensuring precise adaptation to the device's multimodal adjustment module. The device's hardware structure remains unchanged; only the parameter matching logic in the working principle is optimized, as detailed below:

[0089] Principle and logic adjustment: Refine the regulation strategy corresponding to the ratio of neural activity. When the ratio is 1.8-2.2 (mild sympathetic excitation), only the transcutaneous electrical nerve stimulation unit (5-8Hz, 0.3-0.5V) and the thermoregulation unit (37.5℃) are activated for coordinated regulation. When the ratio is >2.2 (severe sympathetic excitation), the three regulation units are activated in synergy, with transcutaneous electrical nerve stimulation (1-3Hz, 0.1-0.3V) and low-frequency magnetic therapy (0.5-2Hz, 0.3-0.3V) activated. The system is linked to the transcutaneous electrical stimulation (TES) (60-80Hz, 2-2.5V) and the temperature sensation (35.5℃) when the ratio is 1.0-1.2 (mild parasympathetic inhibition); when the ratio is <1.0 (severe parasympathetic inhibition), the three units work together, with the transcutaneous electrical stimulation (TES) (80-100Hz, 2.5-3V), low-frequency magnetic therapy (25-30Hz, 0.25-0.3T), and the temperature sensation (35℃).

[0090] Synergistic effect: By refining the principle adjustment logic, the device's multiple adjustment units can be activated on demand, avoiding resource waste and overstimulation. At the same time, the adjustment intensity can be accurately adapted to different levels of disorder. The device hardware's multi-level parameter capability provides support for the principle's graded adjustment. The synergy between the two further improves the adjustment accuracy, reduces health risks, and is suitable for user scenarios with different levels of disorder.

[0091] Example 3

[0092] This embodiment strengthens the device's safety protection hardware and optimizes the safety closed-loop logic in the principle, as detailed below:

[0093] Device hardware optimization: The safety protection unit 43 adds a skin contact detection function to monitor the contact resistance between the transcutaneous electrical nerve stimulation unit electrode and the skin. When the resistance is greater than 10kΩ, it is judged as poor contact. An overheat protection circuit is added to monitor the temperature of the temperature sensing adjustment unit and the internal temperature of the wearer. When the temperature exceeds 42℃ or 45℃, protection is triggered. An emergency stop button is added, independent of the existing button, so that users can quickly cut off all functions when they suddenly feel unwell.

[0094] Optimized Logic: A safety monitoring node is added to the closed-loop process, working in conjunction with the device's safety hardware. When abnormal contact resistance occurs, the electrical stimulation output is immediately stopped, prompting the user to adjust the wearing position, while maintaining the operation of monitoring and other adjustment units. In case of overheating, the power supply to the temperature-sensing adjustment unit is cut off, while the electrical stimulation and magnetic therapy units are retained (with reduced intensity). Upon triggering the emergency stop button, the power supply to all modules is immediately cut off, retaining only the alarm function. This embodiment, through the collaboration of safety hardware and the principle-based safety node, constructs multiple safety defenses to ensure the safety of the software and hardware working together, making it suitable for special populations such as the elderly and children.

[0095] All aspects not detailed in this invention are conventional technical means known to those skilled in the art.

[0096] The above content shows and describes the basic principles, main features, and beneficial effects of the present invention. The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A wearable device for monitoring and regulating the autonomic nervous system, characterized in that, The device, designed to fit the head, neck, chest, and back, integrates a multimodal monitoring module, a multimodal adjustment module, an intelligent control module, and a power supply module. These modules are electrically connected via a flexible printed circuit board (FPC) to form a collaborative working unit. The multimodal monitoring module integrates at least an electrocardiogram (ECG) sensor and a transcutaneous electrical response (TEG) sensor to simultaneously collect two or more physiological signals related to the vegetative-neural system and transmit them to the intelligent control module. The intelligent control module incorporates a vegetative-neural state assessment model to analyze and process the physiological signals in real time, obtaining a quantified assessment of vegetative-neural function. Based on the assessment results, it dynamically generates appropriate adjustment parameters and sends them to the multimodal adjustment module. The multimodal adjustment module integrates at least a transcutaneous electrical nerve stimulation (TENS) unit and a thermosensitive adjustment unit to output two or more synergistic adjustment signals based on the adjustment parameters, targeting and intervening in vegetative-neural function.

2. The wearable device for monitoring and regulating the autonomic nervous system according to claim 1, characterized in that, The multimodal monitoring module also includes a respiratory rate sensor integrated into the wearer at the corresponding chest position, with a measurement range of 10-60 breaths / minute; an electrocardiogram sensor attached to the carotid artery, with a sampling rate of 250-500Hz; and a skin conductance sensor attached to the skin behind the ear, with a measurement range of 0-50μS.

3. The wearable device for monitoring and regulating the autonomic nervous system according to claim 1 or 2, characterized in that, The multimodal adjustment module also includes a low-frequency pulse magnetic therapy unit with a magnetic field strength adjustment range of 0.05-0.5T and a frequency of 0.5-50Hz, which works in conjunction with the transcutaneous electrical nerve stimulation unit and the temperature sensing adjustment unit; the transcutaneous electrical nerve stimulation unit outputs a voltage range of 0.1-5V and a frequency of 1-100Hz; the temperature sensing adjustment unit has an adjustment range of 32-40℃.

4. The wearable device for monitoring and regulating the autonomic nervous system according to claim 3, characterized in that, The evaluation model of the intelligent control module is constructed based on the random forest algorithm. It takes ECG, skin conductance, and respiratory rate characteristic parameters as inputs and outputs the ratio of sympathetic and parasympathetic nerve activity. The built-in parameter matching algorithm calls the preset individual adaptation parameter library based on the evaluation results and dynamically adjusts the output parameters of the multimodal adjustment module, with a data processing delay of ≤1s.

5. The wearable device for monitoring and regulating the autonomic nervous system according to any one of claims 1, 2, and 4, characterized in that, The main body of the wearer is made of flexible silicone material, with a built-in memory metal bracket. The fitting area is provided with ventilation holes with a diameter of 0.5-1mm, and adjustable straps are provided on both sides.

6. The wearable device for monitoring and regulating the vegetative nervous system according to claim 5, characterized in that, The electrodes of the transcutaneous electrical nerve stimulation unit are made of medical-grade silver chloride material, with an electrode area of ​​1-2 cm², and coated with a conductive gel of 0.1-0.2 mm thickness at the skin contact point.

7. The wearable device for monitoring and regulating the autonomic nervous system according to any one of claims 1, 2, 4, and 6, characterized in that, It also includes an interactive module, which integrates an OLED display screen and buttons. The display screen is used to show the vegetative-nervous system status assessment results, adjustment parameters and power levels in real time, while the buttons are used to switch working modes and start / stop adjustment functions.

8. The wearable device for monitoring and regulating the vegetative nervous system according to claim 7, characterized in that, The intelligent control module also has a built-in safety protection unit. When an abnormal physiological signal with a heart rate >120 beats / minute or <50 beats / minute is detected, or when the output parameters of the adjustment module exceed the safety threshold, the adjustment function will be stopped immediately and an audible and visual alarm will be issued.

9. The working principle of a wearable device for monitoring and regulating the autonomic nervous system, characterized in that, The wearable device for monitoring and regulating the autonomic nervous system as described in any one of claims 1-8, relying on a multimodal hardware and software collaborative architecture, realizes the full-process linkage of "signal acquisition - quantitative evaluation - dynamic adjustment - closed-loop feedback", specifically including the following core steps: 1) The multimodal monitoring module synchronously acquires human electrocardiogram and skin conductance signals, which are then filtered, amplified, and preprocessed before being transmitted to the intelligent control module; 2) The intelligent control module extracts signal feature parameters through an evaluation model, calculates the ratio of sympathetic to parasympathetic nerve activity, and quantitatively evaluates the functional state of the autonomic nervous system; 3) Based on the evaluation results, adaptive regulation parameters are dynamically generated, and the multimodal regulation module is controlled to output synergistic regulation signals to target and intervene in nerve function; 4) Physiological signals during the regulation process are continuously acquired and fed back to the intelligent control module in real time to dynamically adjust the regulation parameters and form a closed-loop control.

10. The working principle according to claim 9, characterized in that, In step 2, the normal range for the ratio of sympathetic to parasympathetic nerve activity is set to 1.2-1.

8. When the ratio is >1.8, the transcutaneous electrical nerve stimulation unit outputs a low-frequency signal of 1-10Hz, and the temperature-sensing adjustment unit maintains a constant temperature of 37-38℃ to synergistically inhibit sympathetic nerve activity. When the ratio is <1.2, the transcutaneous electrical nerve stimulation unit outputs a high-frequency signal of 50-100Hz, and the temperature-sensing adjustment unit maintains a constant temperature of 35-36℃ to synergistically activate the parasympathetic nerve.

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