Physical index monitoring system for patient in neurology department

Abstract

The invention discloses a neurology patient body index monitoring system, and particularly relates to the technical field of body monitoring. The environment interaction and adaptation module is used for monitoring and adjusting the surrounding environment of a patient to optimize the health state of the nervous system; the emotion and psychological state monitoring module is used for evaluating the emotion and psychological state of the patient in real time by utilizing an advanced sensing technology and data analysis; and the cognitive function and learning support module is used for monitoring and promoting the cognitive function of the patient to improve neuroplasticity and cognitive ability through interaction and training. By integrating the environment interaction and adaptation module, the emotion and psychological state monitoring module, the cognitive function and learning support module and the comprehensive health ecosystem module, intelligent adjustment of the surrounding environment of a patient, real-time monitoring of the emotion and psychological state, improvement of the cognitive function and comprehensive integration of health resources are achieved; the system optimizes the environmental comfort through intelligent illumination, noise monitoring and air quality adjustment.

Description

Technical Field

[0001] The present invention relates to the technical field of body monitoring, and in particular to a body index monitoring system for neurology patients. Background Art

[0002] As the number of patients with neurological diseases increases year by year, how to improve the quality of life and health of patients through efficient monitoring systems has become an important issue in the medical field. Traditional neurological patient monitoring methods mostly rely on single physiological index detection, such as blood pressure, heart rate, etc. Although these methods can provide certain health information, they cannot fully and real-time reflect the changes in patients' emotions, psychological states and cognitive abilities. The limitations of this single monitoring method often lead to doctors' lack of comprehensive understanding of the patient's overall health status during diagnosis and treatment.

[0003] At the same time, the treatment of modern neurological diseases often requires comprehensive consideration of multiple factors such as the patient's physiology, psychology, and cognition. Traditional monitoring methods are too simple and not accurate enough. During the treatment process, patients often experience emotional fluctuations, psychological pressure, and cognitive function degradation. The existing technology has great deficiencies in dealing with these problems, especially in the intervention methods of emotional regulation and cognitive ability improvement. The existing health monitoring equipment lacks effective multi-source signal acquisition and real-time feedback mechanisms, and cannot make timely and personalized interventions for changes in the patient's physiological and psychological state. There is a lack of a comprehensive system that can simultaneously evaluate and regulate the emotional state, cognitive ability, and physiological indicators of neurological patients, and there is also a lack of solutions that can deeply integrate multiple monitoring data and provide personalized feedback. Therefore, we provide a physical indicator monitoring system for neurological patients. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a physical index monitoring system for neurology patients.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A physical indicator monitoring system for neurology patients, including an environmental interaction and adaptation module for monitoring and adjusting the patient's surrounding environment to optimize the health status of the nervous system, an emotion and psychological state monitoring module for evaluating the patient's emotion and psychological state in real time using advanced sensing technology and data analysis, a cognitive function and learning support module for monitoring and promoting the patient's cognitive function to enhance neural plasticity and cognitive ability through interaction and training, and a comprehensive health ecosystem module for building a comprehensive health ecosystem that integrates various health data and resources and provides all-round support and management.

[0007] The present invention is further configured as follows: the environmental interaction and adaptation module includes an intelligent lighting adjustment module for automatically adjusting the indoor light intensity and color temperature according to the patient's biological clock and real-time activities, an environmental noise monitoring module for real-time monitoring of the ambient noise level, identifying potential noise interference sources, and prompting adjustments through noise reduction technology or an alarm system, a control quality monitoring module for monitoring pollutants, humidity and temperature in the air, an indoor intelligent temperature control module for automatically adjusting the indoor temperature, and a dynamic environmental adaptation module for dynamically adjusting environmental settings according to the patient's activity status and physiological indicators;

[0008] The emotion and psychological state monitoring module includes a facial expression recognition module for analyzing the patient's facial expressions through a camera, a speech emotion analysis module for analyzing the patient's voice intonation to detect emotional fluctuations and stress levels, a biofeedback module for using heart rate variability physiological indicators to provide real-time feedback on the patient's stress and relaxation status, a mental health assessment module for regularly monitoring the patient's mental health status through questionnaires and interactive assessments, and a social interaction monitoring module for tracking the frequency and quality of the patient's social activities to assess the impact of social support on their psychological state.

[0009] The present invention is further configured as follows: the cognitive function and learning support module includes a cognitive ability assessment module for regularly conducting cognitive tests such as memory, attention and executive function to assess the cognitive health of patients, a brain wave stimulation module for promoting neuroplasticity using transcranial magnetic stimulation technology, a virtual reality training module for providing cognitive training and rehabilitation exercises through a VR environment, a personalized learning plan module for formulating personalized learning and training plans based on the patient's cognitive assessment results, and a real-time feedback and incentive module for providing real-time learning progress feedback and incentive mechanisms;

[0010] The comprehensive health ecosystem module includes a cross-platform data integration module for aggregating data from different devices and applications onto a unified platform, a personalized health recommendation module for providing personalized health advice on diet, exercise, and sleep based on comprehensive data analysis, a health resource connection module for connecting patients with medical resources, rehabilitation centers, and psychological counseling services, an intelligent reminder and schedule management module for automatically scheduling and reminding patients of their medication, appointments, and daily exercise activities, and a community support and interaction module for creating a patient community platform to promote communication and support between patients.

[0011] The present invention is further configured as follows: the biofeedback module includes a multi-source physiological signal acquisition module for simultaneously acquiring multiple physiological signals, a signal quality monitoring and correction module for real-time monitoring of the quality of the acquired signals for noise filtering and correction, a multi-dimensional feature extraction and fusion module for extracting key features from various physiological signals and performing multi-dimensional feature fusion to generate comprehensive physiological indicators, a real-time state determination module for determining the user's current physiological and psychological state in real time according to the fused comprehensive physiological indicators, a feedback generation and adjustment module for generating personalized multi-modal feedback content according to the determination results and dynamically adjusting the feedback intensity and type, and a symptomatic intervention measure generation module for generating different solutions and measures according to different states of the user.

[0012] The present invention is further configured as follows: the multi-source physiological signal acquisition module transmits the collected original physiological signals to the signal quality monitoring and correction module; the signal quality monitoring and correction module performs noise filtering and correction on the collected signals, and then provides the purified signals to the multi-dimensional feature extraction and fusion module.

[0013] The present invention is further configured as follows: the multidimensional feature extraction and fusion module extracts key features from the corrected signal and fuses them to generate comprehensive physiological indicators, and then passes these indicators to the real-time status determination module; the real-time status determination module determines the user's status in real time based on the comprehensive physiological indicators, and sends the determination result to the feedback generation and adjustment module; the feedback generation and adjustment module generates personalized feedback based on the determination result, and at the same time passes the user status information to the symptomatic intervention measure generation module.

[0014] The present invention is further configured as follows: after the intelligent lighting adjustment module automatically adjusts the indoor light intensity and color temperature according to the patient's biological clock and real-time activities, the adjustment information is transmitted to the environmental noise monitoring module to synchronously optimize the environmental comfort; after the environmental noise monitoring module monitors the noise level in real time and identifies potential noise interference sources, the noise data is provided to the control quality monitoring module to comprehensively monitor the environmental quality; the control quality monitoring module monitors pollutants, humidity and temperature in the air, and transmits these data to the indoor intelligent temperature control module to achieve automatic temperature adjustment; after the indoor intelligent temperature control module automatically adjusts the indoor temperature according to the data provided by the control quality monitoring module, the temperature adjustment information is sent to the dynamic environment adaptation module to further optimize the environmental settings; after the dynamic environment adaptation module dynamically adjusts the environmental settings according to the patient's activity status and physiological indicators, the adjustment results are fed back to the intelligent lighting adjustment module.

[0015] The present invention is further configured as follows: the facial expression recognition module analyzes the patient's facial expression through a camera to identify emotional changes, and then passes the emotional data to the voice emotion analysis module; the voice emotion analysis module analyzes the patient's voice intonation to detect emotional fluctuations and stress levels, and then provides the emotion and stress data to the biofeedback module to provide real-time feedback on stress and relaxation status; the biofeedback module uses heart rate variability physiological indicators to provide real-time feedback on the patient's stress and relaxation status, and then passes these physiological feedback data to the mental health assessment module to assess the mental health status; the mental health assessment module monitors the patient's mental health status through regular questionnaires and interactive assessments, and then provides the assessment results to the social interaction monitoring module to assess the impact of social support on the mental state; the social interaction monitoring module tracks the frequency and quality of the patient's social activities to assess the impact of social support on his or her mental state, and then feeds back the social support information to the facial expression recognition module.

[0016] The present invention is further configured as follows: after the cognitive ability assessment module regularly conducts cognitive tests such as memory, attention and executive function to assess the patient's cognitive health, the assessment results are transmitted to the brain wave stimulation module to guide the promotion of neural plasticity; after the brain wave stimulation module promotes neural plasticity using transcranial magnetic stimulation technology, the stimulation effect is fed back to the virtual reality training module to optimize cognitive training; after the virtual reality training module provides cognitive training and rehabilitation exercises through a VR environment, the training data is transmitted to the personalized learning plan module to formulate a personalized learning and training plan; after the personalized learning plan module formulates a personalized learning and training plan according to the patient's cognitive assessment results, the plan details are provided to the real-time feedback and incentive module to provide real-time learning progress feedback and incentives; after the real-time feedback and incentive module provides real-time learning progress feedback and incentives, the feedback information is transmitted to the cognitive ability assessment module to continuously evaluate and adjust cognitive training.

[0017] The present invention is further configured as follows: after the cross-platform data integration module aggregates the data from different devices and applications onto a unified platform, the integrated data is provided to the personalized health recommendation module to generate personalized health recommendations on diet, exercise, and sleep; after the personalized health recommendation module provides personalized health recommendations based on comprehensive data analysis, the recommendations are passed to the intelligent reminder and schedule management module to assist in automatically arranging and reminding patients of daily activities such as taking medicine, making appointments, and exercising; after the intelligent reminder and schedule management module automatically arranges and reminds patients of daily activities such as taking medicine, making appointments, and exercising, the reminder information is passed to the health resource connection module to ensure that the patient obtains the required medical resources in a timely manner; after the health resource connection module connects the patient with medical resources, rehabilitation centers, and psychological counseling services, the resource information is provided to the community support and interaction module to promote communication and support between patients; after the community support and interaction module creates a patient community platform to promote communication and support between patients, the community interaction data is fed back to the cross-platform data integration module.

[0018] The beneficial effects of the present invention are:

[0019] 1. The present invention realizes intelligent regulation of the patient's surrounding environment, real-time monitoring of emotions and psychological states, improvement of cognitive functions and comprehensive integration of health resources by integrating environmental interaction and adaptation modules, emotion and psychological state monitoring modules, cognitive function and learning support modules and comprehensive health ecosystem modules. The system optimizes environmental comfort through intelligent lighting, noise monitoring and air quality regulation; dynamically evaluates and relieves patients' emotional fluctuations and psychological pressure by combining facial expression analysis, voice emotion analysis and biofeedback modules; promotes neural plasticity and cognitive ability through cognitive assessment and virtual reality training; integrates data to generate personalized health advice and provides medical resource support, significantly improving patients' quality of life and neurological health level.

[0020] 2. The present invention generates comprehensive physiological indicators such as stress and relaxation state indexes through multi-source physiological signal acquisition, signal quality monitoring and correction, multi-dimensional feature extraction and fusion, and evaluates the patient's physiological and psychological state in real time. Based on the state judgment results, the module provides dynamic multimodal feedback, such as deep breathing guidance, soothing music and vibration prompts. At the same time, through the symptomatic intervention measure generation module, relaxation training or alarm notification is implemented to accurately relieve psychological pressure, enhance emotional stability and self-regulation ability. The system not only improves the patient's neurological health through dynamic monitoring and personalized feedback intervention, but also improves their overall quality of life and health management capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the system modules in the present invention.

[0022] Figure 2It is a schematic diagram of the biofeedback module flow in the present invention. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0024] Example 1

[0025] like Figure 1 As shown, a system for monitoring physical indicators of patients in neurology department includes an environmental interaction and adaptation module for monitoring and adjusting the patient's surrounding environment to optimize the health status of the nervous system, an emotion and psychological state monitoring module for evaluating the patient's emotion and psychological state in real time by using advanced sensing technology and data analysis, a cognitive function and learning support module for monitoring and promoting the patient's cognitive function to improve neural plasticity and cognitive ability through interaction and training, and a comprehensive health ecosystem module for building a comprehensive health ecosystem, integrating various health data and resources, and providing all-round support and management;

[0026] The environmental interaction and adaptation module includes an intelligent lighting adjustment module for automatically adjusting the indoor light intensity and color temperature according to the patient's biological clock and real-time activities, an environmental noise monitoring module for real-time monitoring of ambient noise levels, identifying potential noise interference sources, and prompting adjustments through noise reduction technology or an alarm system, a control quality monitoring module for monitoring pollutants, humidity and temperature in the air, an indoor intelligent temperature control module for automatically adjusting the indoor temperature, and a dynamic environmental adaptation module for dynamically adjusting environmental settings according to the patient's activity status and physiological indicators;

[0027] The emotion and psychological state monitoring module includes a facial expression recognition module for analyzing the patient's facial expression through a camera, a voice emotion analysis module for analyzing the patient's voice intonation to detect emotional fluctuations and stress levels, a biofeedback module for using heart rate variability physiological indicators to provide real-time feedback on the patient's stress and relaxation status, a mental health assessment module for regularly monitoring the patient's mental health status through questionnaires and interactive assessments, and a social interaction monitoring module for tracking the frequency and quality of the patient's social activities to assess the impact of social support on their psychological state;

[0028] The cognitive function and learning support module includes a cognitive ability assessment module for regularly conducting cognitive tests such as memory, attention and executive function to assess the patient's cognitive health,

[0029] A brainwave stimulation module that uses transcranial magnetic stimulation technology to promote neuroplasticity, a virtual reality training module for providing cognitive training and rehabilitation exercises through a VR environment, a personalized learning plan module for developing personalized learning and training plans based on the patient's cognitive assessment results, and a real-time feedback and incentive module for providing real-time learning progress feedback and incentive mechanisms;

[0030] The integrated health ecosystem module includes a cross-platform data integration module for aggregating data from different devices and applications into a unified platform, a personalized health recommendation module for providing personalized health advice on diet, exercise, and sleep based on comprehensive data analysis, a health resource connection module for connecting patients with medical resources, rehabilitation centers, and psychological counseling services, an intelligent reminder and schedule management module for automatically scheduling and reminding patients of medication, appointments, and daily exercise activities, and a community support and interaction module for creating a patient community platform to promote communication and support between patients;

[0031] After the intelligent light adjustment module automatically adjusts the indoor light intensity and color temperature according to the patient's biological clock and real-time activities, the adjustment information is transmitted to the environmental noise monitoring module to synchronously optimize the environmental comfort; after the environmental noise monitoring module monitors the noise level in real time and identifies potential noise interference sources, the noise data is provided to the control quality monitoring module to comprehensively monitor the environmental quality; the control quality monitoring module monitors pollutants, humidity and temperature in the air, and transmits these data to the indoor intelligent temperature control module to achieve automatic temperature adjustment; after the indoor intelligent temperature control module automatically adjusts the indoor temperature according to the data provided by the control quality monitoring module, the temperature adjustment information is sent to the dynamic environment adaptation module to further optimize the environmental settings; after the dynamic environment adaptation module dynamically adjusts the environmental settings according to the patient's activity status and physiological indicators, the adjustment results are fed back to the intelligent light adjustment module;

[0032] The facial expression recognition module analyzes the patient's facial expression through a camera to identify emotional changes, and then passes the emotional data to the voice emotion analysis module; the voice emotion analysis module analyzes the patient's voice intonation to detect emotional fluctuations and stress levels, and then provides the emotional and stress data to the biofeedback module to provide real-time feedback on stress and relaxation status; the biofeedback module uses heart rate variability physiological indicators to provide real-time feedback on the patient's stress and relaxation status, and then passes these physiological feedback data to the mental health assessment module to assess the mental health status; the mental health assessment module monitors the patient's mental health status through regular questionnaires and interactive assessments, and then provides the assessment results to the social interaction monitoring module to assess the impact of social support on the mental state; the social interaction monitoring module tracks the frequency and quality of the patient's social activities to assess the impact of social support on his or her mental state, and then feeds back the social support information to the facial expression recognition module;

[0033] After the cognitive ability assessment module regularly conducts cognitive tests such as memory, attention and executive function to assess the patient's cognitive health, the assessment results are passed to the brain wave stimulation module to guide the promotion of neural plasticity; after the brain wave stimulation module promotes neural plasticity using transcranial magnetic stimulation technology, the stimulation effect is fed back to the virtual reality training module to optimize cognitive training; after the virtual reality training module provides cognitive training and rehabilitation exercises through a VR environment, the training data is passed to the personalized learning plan module to formulate a personalized learning and training plan; after the personalized learning plan module formulates a personalized learning and training plan based on the patient's cognitive assessment results, the plan details are provided to the real-time feedback and incentive module to provide real-time learning progress feedback and incentives; after the real-time feedback and incentive module provides real-time learning progress feedback and incentives, the feedback information is passed to the cognitive ability assessment module to continuously evaluate and adjust cognitive training;

[0034] After the cross-platform data integration module aggregates the data from different devices and applications onto a unified platform, it provides the integrated data to the personalized health recommendation module to generate personalized health recommendations on diet, exercise, and sleep; after the personalized health recommendation module provides personalized health recommendations based on comprehensive data analysis, it passes the recommendations to the intelligent reminder and schedule management module to assist in automatically arranging and reminding patients of daily activities such as taking medication, making appointments, and exercising; after the intelligent reminder and schedule management module automatically arranges and reminds patients of daily activities such as taking medication, making appointments, and exercising, it passes the reminder information to the health resource connection module to ensure that patients obtain the required medical resources in a timely manner; after the health resource connection module connects patients with medical resources, rehabilitation centers, and psychological counseling services, it provides resource information to the community support and interaction module to promote communication and support between patients; after the community support and interaction module creates a patient community platform to promote communication and support between patients, it feeds back the community interaction data to the cross-platform data integration module.

[0035] In the above embodiment, the system uses the intelligent light adjustment module to automatically adapt to the indoor light and improve the comfort level according to the patient's biological clock; real-time voice emotion analysis and biofeedback help identify and relieve emotional fluctuations and stress; provide cognitive training through virtual reality training modules to promote brain plasticity and improve learning ability; the integrated health data platform provides personalized health advice and connects medical resources, while establishing community support and enhancing the patient's social experience. The synergy of all modules significantly improves the patient's quality of life, improves the level of neurological health, and achieves personalized dynamic optimization through continuous feedback.

[0036] Example 2

[0037] like Figure 1-2As shown, a physical index monitoring system for neurology patients, the biofeedback module includes a multi-source physiological signal acquisition module for simultaneously acquiring multiple physiological signals, a signal quality monitoring and correction module for real-time monitoring of the quality of the acquired signals for noise filtering and correction, a multi-dimensional feature extraction and fusion module for extracting key features from various physiological signals and performing multi-dimensional feature fusion to generate comprehensive physiological indicators, a real-time state determination module for determining the current physiological and psychological state of the user in real time according to the fused comprehensive physiological indicators, a feedback generation and adjustment module for generating personalized multi-modal feedback content according to the determination result and dynamically adjusting the feedback intensity and type, and a symptomatic intervention measure generation module for generating different solutions and measures according to different states of the user;

[0038] The multi-source physiological signal acquisition module transmits the collected original physiological signals to the signal quality monitoring and correction module; after the signal quality monitoring and correction module performs noise filtering and correction on the collected signals, the purified signals are provided to the multi-dimensional feature extraction and fusion module, which extracts key features from the corrected signals and fuses them to generate comprehensive physiological indicators, and then transmits these indicators to the real-time status determination module; the real-time status determination module determines the user's status in real time according to the comprehensive physiological indicators, and sends the determination result to the feedback generation and adjustment module; the feedback generation and adjustment module generates personalized feedback according to the determination result, and at the same time transmits the user status information to the symptomatic intervention measures generation module.

[0039] In the above embodiment, the biofeedback module collects a variety of physiological signals (heart rate, skin conductance, etc.), and uses the signal quality monitoring and correction module to filter noise and correct data to ensure signal accuracy; then, the multidimensional feature extraction and fusion module extracts key features and fuses them to generate comprehensive physiological indicators, such as quantitative indexes of stress and relaxation status; these indicators accurately evaluate the patient's current physiological and psychological state through the real-time state determination module. Based on the determination results, the feedback generation and adjustment module provides personalized, multimodal feedback (visual prompts or audio guidance), and passes it to the symptomatic intervention measures generation module to formulate specific solutions, such as relaxation training or emotional management strategies. Through this process, the system can relieve the patient's psychological stress in real time in a dynamic and accurate manner, improve emotional stability, and improve the overall neurological health level, significantly enhancing the patient's self-regulation ability and quality of life.

[0040] The real-time status determination unit classifies the user status into the following categories based on the extracted and fused physiological features, and takes corresponding processing measures:

[0041] 1. High stress state

[0042] Feedback method:

[0043] Dynamic deep breathing guidance: Displays dynamic breathing animation on the screen to guide users to perform deep breathing exercises.

[0044] Soothing music playback: Automatically play soft music or nature sounds to help users relax.

[0045] Vibration reminder: Sends slight vibrations through the wearable device to remind the user to perform relaxation exercises.

[0046] Interventions:

[0047] Automatically notify professionals: If the high-stress condition persists, the system automatically sends an alert to a designated medical or mental health professional.

[0048] Recommended meditation resources: Provide meditation audio or video resources to guide users in meditation practice.

[0049] 2. Moderate stress state

[0050] Feedback method:

[0051] Simple relaxation tips: Display text tips such as "Take a deep breath" or "Try to relax."

[0052] Background music adjustment: Play relaxing background music to create a soothing environment.

[0053] Interventions:

[0054] Suggest a short break: Remind users to take a short break or do some simple stretching exercises.

[0055] Status record: record the current pressure status for subsequent analysis and tracking.

[0056] 3. Low stress state

[0057] Feedback method:

[0058] Positive feedback information: Display positive information such as "You are in good condition now, keep it up!"

[0059] Motivational music: Play upbeat music to enhance the user’s positive emotions.

[0060] Interventions:

[0061] Continuous Monitoring: Keep a constant watch on the user's status to ensure stress levels remain low.

[0062] Health advice push: Send healthy lifestyle advice, such as moderate exercise, good sleep, etc.

[0063] 4. Enhanced state of concentration

[0064] Feedback method:

[0065] Enhance focus prompts: Display or play prompts that encourage users to stay focused, such as "Stay focused, keep going!".

[0066] Reward mechanism: Provide virtual rewards or achievement badges to motivate users to maintain high concentration.

[0067] Interventions:

[0068] Task optimization suggestions: Based on the user's concentration state, it is recommended to adjust the difficulty or pace of the current task.

[0069] Record efficient time periods: Record the time periods when users are highly focused to optimize work or study arrangements.

[0070] 5. Abnormal status (such as data anomaly or equipment failure)

[0071] Feedback method:

[0072] Error message: Displays device abnormality or data error information to the user, prompting them to check the device or restart it.

[0073] Interventions:

[0074] Automatic notification of technical support: The system automatically sends fault reports to the technical support team for inspection and maintenance.

[0075] Start backup plan: Start backup data collection method to ensure continuous operation of the system and data integrity.

[0076] Working principle: When used, the present invention improves the patient's neurological health and quality of life through environmental adjustment, emotional and psychological monitoring, cognitive function training and comprehensive health management. The system optimizes the patient's surrounding environment through environmental interaction modules such as intelligent lighting, noise monitoring, and air quality adjustment. At the same time, it combines facial expressions, voice emotion analysis and biofeedback to evaluate emotions and psychological states in real time, and coordinates cognitive assessment and virtual reality training to improve the patient's neuroplasticity and cognitive ability, and builds a comprehensive health ecosystem through data integration and personalized health recommendations.

[0077] In actual use, the biofeedback module acquires multiple signals such as heart rate and skin conductance in real time through the multi-source physiological signal acquisition module. After being denoised by the signal quality monitoring and correction module, the multi-dimensional feature extraction and fusion module generates comprehensive physiological indicators, such as stress and relaxation state index. These data are parsed into the patient's current physiological and psychological state by the real-time state determination module, and passed to the feedback generation and regulation module to provide dynamic multimodal feedback, such as deep breathing guidance or soothing music. At the same time, the symptomatic intervention measures generation module provides solutions such as relaxation training or alarm notifications according to the state.

[0078] Through multi-level real-time monitoring, precise feedback and dynamic intervention, the system can identify mood swings and relieve psychological stress, promoting patients' emotional stability and self-regulation. At the same time, it provides personalized intervention and resource support for different states, which not only significantly improves the level of neurological health, but also enhances the overall quality of life and health self-management ability of patients.

[0079] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A physical index monitoring system for patients in neurology department, characterized in that: It includes an environmental interaction and adaptation module for monitoring and adjusting the patient's surrounding environment to optimize the health of the nervous system, an emotion and psychological state monitoring module for using advanced sensing technology and data analysis to evaluate the patient's emotions and psychological state in real time, a cognitive function and learning support module for monitoring and promoting the patient's cognitive function to enhance neural plasticity and cognitive ability through interaction and training, and a comprehensive health ecosystem module for building a comprehensive health ecosystem that integrates various health data and resources and provides comprehensive support and management.

2. A neurology patient physical index monitoring system according to claim 1, characterized in that: The environmental interaction and adaptation module includes an intelligent lighting adjustment module for automatically adjusting the indoor light intensity and color temperature according to the patient's biological clock and real-time activities, an environmental noise monitoring module for real-time monitoring of ambient noise levels, identifying potential noise interference sources, and prompting adjustments through noise reduction technology or an alarm system, a control quality monitoring module for monitoring pollutants, humidity and temperature in the air, an indoor intelligent temperature control module for automatically adjusting the indoor temperature, and a dynamic environmental adaptation module for dynamically adjusting environmental settings according to the patient's activity status and physiological indicators; The emotion and psychological state monitoring module includes a facial expression recognition module for analyzing the patient's facial expressions through a camera, a speech emotion analysis module for analyzing the patient's voice intonation to detect emotional fluctuations and stress levels, a biofeedback module for using heart rate variability physiological indicators to provide real-time feedback on the patient's stress and relaxation status, a mental health assessment module for regularly monitoring the patient's mental health status through questionnaires and interactive assessments, and a social interaction monitoring module for tracking the frequency and quality of the patient's social activities to assess the impact of social support on their psychological state.

3. A neurology patient physical index monitoring system according to claim 1, characterized in that: The cognitive function and learning support module includes a cognitive ability assessment module for regularly conducting cognitive tests such as memory, attention and executive function to assess the cognitive health of patients, a brain wave stimulation module for promoting neuroplasticity using transcranial magnetic stimulation technology, a virtual reality training module for providing cognitive training and rehabilitation exercises through a VR environment, a personalized learning plan module for formulating personalized learning and training plans based on the patient's cognitive assessment results, and a real-time feedback and incentive module for providing real-time learning progress feedback and incentive mechanisms; The comprehensive health ecosystem module includes a cross-platform data integration module for aggregating data from different devices and applications onto a unified platform, a personalized health recommendation module for providing personalized health advice on diet, exercise, and sleep based on comprehensive data analysis, a health resource connection module for connecting patients with medical resources, rehabilitation centers, and psychological counseling services, an intelligent reminder and schedule management module for automatically scheduling and reminding patients of their medication, appointments, and daily exercise activities, and a community support and interaction module for creating a patient community platform to promote communication and support between patients.

4. A neurology patient physical index monitoring system according to claim 1, characterized in that: The biofeedback module includes a multi-source physiological signal acquisition module for simultaneously acquiring multiple physiological signals, a signal quality monitoring and correction module for real-time monitoring of the quality of the acquired signals for noise filtering and correction, a multi-dimensional feature extraction and fusion module for extracting key features from various physiological signals and performing multi-dimensional feature fusion to generate comprehensive physiological indicators, a real-time state determination module for determining the user's current physiological and psychological state in real time based on the fused comprehensive physiological indicators, a feedback generation and adjustment module for generating personalized multi-modal feedback content based on the determination results and dynamically adjusting the feedback intensity and type, and a symptomatic intervention measure generation module for generating different solutions and measures according to different states of the user.

5. A neurology patient physical index monitoring system according to claim 4, characterized in that: The multi-source physiological signal acquisition module transmits the collected original physiological signals to the signal quality monitoring and correction module; after the signal quality monitoring and correction module performs noise filtering and correction on the collected signals, the purified signals are provided to the multi-dimensional feature extraction and fusion module.

6. A neurology patient physical index monitoring system according to claim 5, characterized in that: The multi-dimensional feature extraction and fusion module extracts key features from the corrected signal and fuses them to generate comprehensive physiological indicators, and then transmits these indicators to the real-time state determination module; the real-time state determination module determines the user's state in real time according to the comprehensive physiological indicators, and sends the determination result to the feedback generation and adjustment module; The feedback generation and adjustment module generates personalized feedback according to the determination result, and transmits the user status information to the symptomatic intervention measure generation module.

7. A neurology patient physical index monitoring system according to claim 2, characterized in that: After the intelligent lighting adjustment module automatically adjusts the indoor light intensity and color temperature according to the patient's biological clock and real-time activities, the adjustment information is transmitted to the environmental noise monitoring module to synchronously optimize the environmental comfort; after the environmental noise monitoring module monitors the noise level in real time and identifies potential noise interference sources, the noise data is provided to the control quality monitoring module to comprehensively monitor the environmental quality; the control quality monitoring module monitors pollutants, humidity and temperature in the air, and transmits these data to the indoor intelligent temperature control module to realize automatic temperature adjustment; after the indoor intelligent temperature control module automatically adjusts the indoor temperature according to the data provided by the control quality monitoring module, the temperature adjustment information is sent to the dynamic environmental adaptation module to further optimize the environmental settings; after the dynamic environmental adaptation module dynamically adjusts the environmental settings according to the patient's activity status and physiological indicators, the adjustment results are fed back to the intelligent lighting adjustment module.

8. A neurology patient physical index monitoring system according to claim 2, characterized in that: The facial expression recognition module analyzes the patient's facial expression through a camera to identify emotional changes and transmits the emotional data to the voice emotion analysis module; The speech emotion analysis module analyzes the patient's voice intonation to detect emotional fluctuations and stress levels, and provides the emotion and stress data to the biofeedback module to provide real-time feedback on stress and relaxation status; The biofeedback module uses the heart rate variability physiological index to provide real-time feedback on the patient's stress and relaxation status, and then transmits these physiological feedback data to the mental health assessment module to assess the mental health status; the mental health assessment module monitors the patient's mental health status through regular questionnaires and interactive assessments, and then provides the assessment results to the social interaction monitoring module to assess the impact of social support on the mental state; The social interaction monitoring module tracks the frequency and quality of the patient's social activities and assesses the impact of social support on his or her psychological state, and then feeds back the social support information to the facial expression recognition module.

9. A neurology patient physical index monitoring system according to claim 3, characterized in that: The cognitive ability assessment module regularly conducts cognitive tests such as memory, attention and executive function to assess the patient's cognitive health, and then transmits the assessment results to the brain wave stimulation module to guide the promotion of neural plasticity; the brain wave stimulation module uses transcranial magnetic stimulation technology to promote neural plasticity, and then feeds back the stimulation effect to the virtual reality training module to optimize cognitive training; the virtual reality training module provides cognitive training and rehabilitation exercises through a VR environment, and then transmits the training data to the personalized learning plan module to formulate a personalized learning and training plan; After the personalized learning plan module formulates a personalized learning and training plan based on the patient's cognitive assessment results, the plan details are provided to the real-time feedback and incentive module to provide real-time learning progress feedback and incentives; After providing real-time learning progress feedback and motivation, the real-time feedback and motivation module transmits the feedback information to the cognitive ability assessment module to continuously assess and adjust cognitive training.

10. A neurology patient physical index monitoring system according to claim 3, characterized in that: The cross-platform data integration module aggregates data from different devices and applications into a unified platform and provides the integrated data to the personalized health recommendation module to generate personalized health recommendations in terms of diet, exercise, and sleep; After providing personalized health advice based on comprehensive data analysis, the personalized health recommendation module passes the advice to the intelligent reminder and schedule management module to assist in automatically arranging and reminding patients of daily activities such as taking medicine, making appointments, and exercising; after automatically arranging and reminding patients of daily activities such as taking medicine, making appointments, and exercising, the intelligent reminder and schedule management module passes the reminder information to the health resource connection module to ensure that patients obtain the required medical resources in a timely manner; After the health resource connection module connects patients with medical resources, rehabilitation centers, and psychological counseling services, it provides resource information to the community support and interaction module to promote communication and support among patients; After the community support and interaction module creates a patient community platform to promote communication and support between patients, it feeds back the community interaction data to the cross-platform data integration module.

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