Intelligent eyeshade system and method for plateau tourism

Abstract

The invention discloses an intelligent eyeshade system and method for plateau tourism. The intelligent eyeshade system comprises a signal acquisition unit, a signal processing unit and a control unit, the data processing and transmission unit is responsible for performing data processing on the physiological signals acquired by the signal acquisition unit, the data processing comprises signal separation, reconstruction and feature extraction, the processed data is uploaded to a cloud server, and meanwhile, a control signal from the cloud server is received; the sleep guiding and monitoring unit is responsible for receiving a control signal from the cloud, monitoring the sleep of the tourist in real time and starting an early warning function according to a monitoring result; the cloud server is responsible for receiving and storing the processed data provided by the data processing and transmitting unit, mining and analyzing the received processed data of multiple physiological parameters, and customizing a personalized regulation and control scheme according to the altitude stress degree and sleep quality of tourists; and sending the personalized regulation and control scheme to a sleep guiding and monitoring unit.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent sleep for plateau tourism, and in particular to an intelligent eye mask system and method for plateau tourism. Background Art

[0002] With the rapid development of technologies such as the Internet of Things, big data, and artificial intelligence, smart wearable devices have been widely used in the field of medical health. As one of them, smart eye masks combine modern technology with the functions of traditional eye masks. They monitor the user's sleep status in real time through built-in sensors and algorithms, and provide personalized sleep experience based on personal preferences and needs. The maturity of this technology provides strong technical support for the development of the smart eye mask system for plateau tourism.

[0003] In the prior art, altitude sickness is a common health problem in plateau tourism. Each user has different adaptability to the plateau environment and different degrees of altitude sickness. It is difficult for the existing system to segment and optimize according to the degree of the user's altitude sickness. The services provided may lack pertinence and effectiveness, thereby reducing the overall efficiency of the system. Therefore, a plateau tourism smart eye mask system and method are proposed. Summary of the invention

[0004] The purpose of the present invention is to solve the problem in the prior art that each user has different adaptability to the plateau environment and different degrees of altitude sickness. The existing system is difficult to segment and optimize according to the user's altitude sickness degree, so the services provided may lack pertinence and effectiveness, thereby reducing the overall efficiency of the system. The proposed plateau tourism smart eye mask system and method are provided.

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

[0006] Plateau tourism smart eye mask system, including:

[0007] Signal acquisition unit: responsible for collecting electrooculogram, eye movement, respiration and blood oxygen physiological signals using the front-end acquisition chip ADS1299 and the gyroscope MPU-6050 sensor;

[0008] Data processing and transmission unit: responsible for processing the physiological signals collected by the signal acquisition unit through the STM32F2 main controller (MCU), including signal separation, reconstruction and feature extraction, and uploading the processed data to the cloud server using the BLE5.0 Bluetooth transmission method, while receiving control signals from the cloud server;

[0009] Sleep guidance and sleep monitoring unit: responsible for receiving control signals from the cloud, such as personalized control schemes, and real-time monitoring of tourists' sleep, including apnea recognition, blood oxygen saturation monitoring, etc. According to the monitoring results, the corresponding early warning functions are activated, such as vibration reminders, alarm sounds, etc.;

[0010] Cloud server: responsible for receiving and storing processed data from the data processing and transmission unit, mining and analyzing the received processed data of multiple physiological parameters, revealing tourists' sleep status, health status and existing risks, and customizing personalized control plans according to tourists' altitude sickness and sleep quality, aiming to improve tourists' sleep quality and prevent the occurrence of abnormal conditions such as altitude sickness. The personalized control plans are sent to the sleep guidance and sleep monitoring units through the data processing and transmission unit;

[0011] Data Security and Privacy Protection Unit: Responsible for the security and privacy protection of business data during data storage, analysis and processing.

[0012] The above technical solution further includes:

[0013] Furthermore, the signal acquisition unit includes a front-end acquisition subunit, a sensor subunit and a signal preprocessing subunit. The front-end acquisition subunit is responsible for using ADS1299 to collect electrooculogram (EEG) and eye movement (EOG) signals. ADS1299 is a high-precision, low-power 24-bit analog-to-digital converter (ADC), which is particularly suitable for bioelectric signal acquisition. The front-end acquisition subunit transmits the collected electrooculogram and eye movement raw signals to the signal preprocessing subunit. The sensor subunit is responsible for using the gyroscope MPU-6050 sensor to collect breathing signals (by monitoring small movements of the chest), blood oxygen saturation signals (by emitting light of a specific wavelength and measuring the reflection or transmission of light). The intensity of incident light is used to estimate the blood oxygen level) and to assist in the correction of eye movement signals (although the eye movement signals are mainly collected by ADS1299, the accelerometer of MPU-6050 can provide additional movement information). MPU-6050 is used to detect the user's head posture. In this application, the main focus is on its breathing monitoring function. The sensor subunit transmits the collected original breathing signal to the signal preprocessing subunit, and at the same time, transmits the auxiliary eye movement correction information to the signal preprocessing subunit. The signal preprocessing subunit receives the original signals from the front-end acquisition subunit and the sensor subunit, and performs filtering, amplification and denoising. At the same time, eye movement correction is performed according to the eye movement correction information.

[0014] Furthermore, the signal preprocessing subunit performs eye movement correction according to the eye movement correction information, specifically in the following steps:

[0015] Signal reception and integration:

[0016] Receive the original eye movement signal (EOG) from the front-end acquisition subunit and the auxiliary eye movement correction information from the sensor subunit, wherein the eye movement correction information includes acceleration and angular velocity data of the head;

[0017] Signal preprocessing:

[0018] Filtering and amplifying the original eye movement signal and the auxiliary eye movement correction information to remove noise and enhance signal strength;

[0019] State definition and initialization:

[0020] Define the state vector of the eye movement signal, which may include information such as the position and speed of the eyeball, and initialize the state vector and error covariance matrix;

[0021] Kalman filter iteration:

[0022] According to the state transfer matrix and the input control matrix, the eye movement signal state at the next moment is predicted. According to the observation matrix and the observation value, the Kalman gain is calculated. The predicted state is corrected using the Kalman gain and the observation value to obtain the posterior state estimate and update the error covariance matrix.

[0023] Corrected signal output:

[0024] The corrected eye movement signals are output to the data processing and analysis unit. These corrected signals can be used to more accurately analyze the user's eye movements, thereby supporting subsequent sleep monitoring, health assessment and other functions.

[0025] Furthermore, the data processing and transmission unit includes a signal separation subunit, a signal reconstruction and feature extraction subunit and a transmission subunit. The signal separation subunit realizes signal separation through a GPIO (general input and output) module, converts an input signal into multiple output signals to meet the needs of different peripherals or functions. The signal reconstruction and feature extraction subunit utilizes the computing power and related algorithms of STM32F2 to reconstruct the signal and extract features. The reconstructed signal realizes signal denoising and smoothing. The feature extraction is used to extract key information or features in the signal. The transmission subunit is responsible for wireless transmission of data, supports the BLE5.0 standard, and has low power consumption and high With characteristics such as transmission speed, data can be uploaded to the cloud server and control signals from the cloud can be received. STM32F2 realizes signal input and separation by configuring the GPIO module. The separated signal is further processed by STM32F2 or output to other peripherals. STM32F2 uses its own computing power and related algorithms to reconstruct and extract features of the input signal. STM32F2 uploads the processed data to the cloud server through the BLE5.0 Bluetooth transmission subunit. After receiving the data, the cloud server processes, analyzes or makes decisions to generate control signals. The control signals are sent back to STM32F2 through the BLE5.0 Bluetooth transmission subunit to achieve closed-loop control.

[0026] Furthermore, the sleep guidance and sleep monitoring unit includes a data processing and analysis subunit and an early warning execution subunit. The data processing and analysis subunit processes and analyzes the physiological signals collected by the signal acquisition unit to identify apnea and abnormal blood oxygen saturation. The early warning execution subunit accepts a personalized control plan provided by the cloud server, and activates the early warning function according to the personalized control plan and the analysis results of the data processing and analysis subunit. The early warning function includes a vibration reminder and an alarm sound.

[0027] Furthermore, the cloud server includes a data analysis and processing unit, a personalized solution generation unit, a personalized service unit and a remote monitoring and management unit. The data analysis and processing unit is responsible for mining and analyzing the received physiological data, revealing the tourists' sleep status, health status and possible risks, and generating detailed sleep reports and data analysis results. The personalized solution generation unit generates a personalized sleep regulation solution based on the results of data analysis and processing. The personalized service unit sets personalized needs such as sleep goals and warning thresholds. The remote monitoring and management unit is responsible for providing and managing tourists' sleep data, analysis results and personalized regulation solutions.

[0028] Furthermore, the generating of a personalized sleep regulation plan comprises the following specific steps:

[0029] Data collection and preprocessing:

[0030] Collect tourists' electrooculogram, eye movement, respiration and blood oxygen physiological signals, evaluate tourists' altitude sickness according to their subjective feelings (such as headache, nausea, fatigue and other symptoms) and objective physiological indicators (such as the degree of decrease in blood oxygen saturation), and clean, denoise and standardize the collected data to ensure data quality and consistency;

[0031] Data analysis and mining:

[0032] Analyze the correlation between physiological data and the degree of altitude sickness and sleep quality. Based on the data analysis results, identify the possible health risks of tourists, such as severe altitude sickness and sleep disorders. According to the results of correlation analysis and risk identification, build a prediction model to predict the degree of altitude sickness and sleep quality changes that tourists may experience in the future.

[0033] Preset threshold settings:

[0034] Based on professional medical research and data verification, the normal range and abnormal thresholds of heart rate, respiratory rate and blood oxygen saturation physiological indicators are set. Different levels of altitude sickness thresholds are set according to the severity of altitude sickness. The thresholds of good and bad sleep quality are set according to the sleep duration and deep sleep ratio.

[0035] Personalized control plan generation:

[0036] Based on tourists' physiological data, degree of altitude sickness and sleep quality, combined with preset thresholds, personalized control plans are formulated. The plans include adjusting the sleeping environment (such as light, temperature, humidity), providing oxygen supply, recommending drug treatment or psychological counseling, and other measures. The control plans are dynamically adjusted and optimized based on tourists' real-time feedback and changes in physiological data.

[0037] Furthermore, the data security module includes a data encryption unit, an access control unit, a security audit and monitoring unit, a privacy compliance management unit and a data backup and recovery unit. The data encryption unit is responsible for data encryption and decryption. The access control unit is responsible for managing user roles, permissions and identity authentication. The security audit and monitoring unit is responsible for monitoring system logs, detecting abnormal access and potential threats. The privacy compliance management unit ensures that system operations comply with privacy regulations and processes user privacy data. The data backup and recovery unit is responsible for regular data backup and disaster recovery plans. Before data storage, the data encryption unit encrypts the data and then passes the encrypted data to the data center for storage. The access control unit controls access to encrypted data and unencrypted data based on the user's role and permissions. When a user requests access to data, the access control unit first verifies the user's permissions and then allows or denies the access request. The security audit and monitoring unit monitors the system log in real time, including the access records of the access control unit and the data operation records of the data center. The data backup and recovery unit regularly copies data from the data center and stores it in a secure location.

[0038] The method of the plateau tourism intelligent eye mask system comprises the following steps:

[0039] Correctly wear the eye mask: The user needs to wear the smart eye mask on the eyes, ensuring that the eye mask fits tightly against the face to avoid light leakage or looseness. The signal acquisition unit detects the wearing status of the eye mask. If it detects that it is not worn correctly, it will vibrate to prompt the user to adjust it.

[0040] Receive and store personalized settings: Users send personalized settings to the sleep guidance and sleep monitoring units through the cloud server, including sleep goals, warning thresholds (such as apnea time, blood oxygen saturation lower limit, etc.);

[0041] Check sensor contact: Check the contact between the sensor and the user's skin to ensure the accuracy of data collection. If poor sensor contact is detected, the user will be prompted to adjust the wearing position of the eye mask through voice or vibration;

[0042] Start data collection: Users can start the signal collection unit through the mobile phone APP or the physical button on the eye mask to collect electrooculogram signals, eye movement signals, breathing signals and blood oxygen signals;

[0043] Data preprocessing: The collected signals are separated, reconstructed, and feature extracted to improve the accuracy and reliability of the data. The preprocessed data will be uploaded to the cloud server via BLE5.0 Bluetooth transmission;

[0044] Cloud processing and analysis: The cloud server processes and analyzes the received data to extract useful sleep information. The analysis results will be used for subsequent sleep monitoring and regulation;

[0045] Determine awake state: Determine whether the user is awake based on the collected physiological signals. If the user is awake, the sleep guidance program will be activated to help the user fall asleep quickly by playing soft music or sounds;

[0046] Check the wearing status again: After starting the sleep guidance program, check the wearing status of the eye mask again to ensure the sleep guidance effect;

[0047] Sleep apnea recognition: When the user falls asleep, the sleep guidance program stops and the sleep apnea recognition function is activated to determine whether the user has apnea by monitoring the breathing signal in real time;

[0048] Vibration and alarm: If the duration of apnea is detected to exceed the preset threshold (such as 5 seconds), the vibrator will be activated and an alarm will sound. The user can judge whether he / she has apnea based on the vibration and the alarm sound, and adjust his / her sleeping position or perform other necessary operations in time.

[0049] Respiration recovery judgment: After vibration and alarm, judge again whether the user's breathing is normal. If the breathing is restored to normal, stop vibration and alarm. If the breathing is still abnormal, continue vibration and alarm until the user takes measures to solve the problem;

[0050] Stop monitoring and regulation: When the user wakes up or the system detects that the user has left the sleeping state, all monitoring and regulation functions are stopped.

[0051] The present invention has the following beneficial effects:

[0052] 1. In the present invention, the cloud server can customize personalized control plans according to the tourists' altitude sickness degree and key information of sleep quality. These plans not only take into account the individual differences of tourists, but also combine the particularity of the plateau environment, thereby ensuring the effectiveness and pertinence of the control plans.

[0053] 2. In the present invention, multiple physiological parameters such as electrooculography, eye movement, respiration and blood oxygen can be monitored simultaneously, realizing comprehensive collection and fusion of information, and can more accurately reflect the sleep state and physiological condition of tourists.

[0054] 3. In the present invention, according to the physiological signals and sleep status of tourists, a personalized sleep regulation plan is provided, such as adjusting the breathing frequency, improving the sleeping posture, etc. When tourists have altitude sickness or other abnormal conditions, an early warning signal can be issued in time to effectively ensure the safety of tourists. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A system block diagram of the plateau tourism intelligent eye mask system and method proposed by the present invention;

[0056] Figure 2 The present invention provides a flow chart of the intelligent eye mask system and method for plateau tourism. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] See also Figure 1-Figure 2 As shown, the present invention is a plateau tourism intelligent eye mask system, comprising:

[0059] Signal acquisition unit: responsible for collecting electrooculogram, eye movement, respiration and blood oxygen physiological signals using the front-end acquisition chip ADS1299 and the gyroscope MPU-6050 sensor;

[0060] Data processing and transmission unit: responsible for processing the physiological signals collected by the signal acquisition unit through the STM32F2 main controller (MCU). Data processing includes signal separation, reconstruction and feature extraction, and uploading the processed data to the cloud server using BLE5.0 Bluetooth transmission, while receiving control signals from the cloud server;

[0061] Sleep guidance and sleep monitoring unit: responsible for receiving control signals from the cloud, such as personalized control schemes, and real-time monitoring of tourists' sleep, including apnea recognition, blood oxygen saturation monitoring, etc. According to the monitoring results, the corresponding early warning functions are activated, such as vibration reminders, alarm sounds, etc.;

[0062] Cloud server: responsible for receiving and storing processed data from the data processing and transmission unit, mining and analyzing the received processed data of multiple physiological parameters, revealing tourists' sleep status, health status and existing risks, and customizing personalized control plans according to tourists' altitude sickness and sleep quality, aiming to improve tourists' sleep quality and prevent the occurrence of abnormal conditions such as altitude sickness. The personalized control plans are sent to the sleep guidance and sleep monitoring units through the data processing and transmission unit;

[0063] Data Security and Privacy Protection Unit: Responsible for the security and privacy protection of business data during data storage, analysis and processing.

[0064] In one embodiment, for the above-mentioned signal acquisition unit, the signal acquisition unit includes a front-end acquisition subunit, a sensor subunit and a signal preprocessing subunit. The front-end acquisition subunit is responsible for using ADS1299 to collect electrooculogram (EEG) and eye movement (EOG) signals. ADS1299 is a high-precision, low-power 24-bit analog-to-digital converter (ADC), which is particularly suitable for bioelectric signal acquisition. The front-end acquisition subunit transmits the collected electrooculogram and eye movement raw signals to the signal preprocessing subunit. The sensor subunit is responsible for using the gyroscope MPU-6050 sensor to collect breathing signals (by monitoring tiny movements of the chest), blood oxygen saturation signals (by emitting light of a specific wavelength and Measuring the intensity of reflected or transmitted light to estimate blood oxygen level) and assisting in the correction of eye movement signals (although eye movement signals are mainly collected by ADS1299, the accelerometer of MPU-6050 can provide additional motion information). MPU-6050 is used to detect the user's head posture. In this application, the main focus is on its respiratory monitoring function. The sensor subunit transmits the collected original respiratory signal to the signal preprocessing subunit. At the same time, the auxiliary eye movement correction information is transmitted to the signal preprocessing subunit. The signal preprocessing subunit receives the original signals from the front-end acquisition subunit and the sensor subunit, and performs filtering, amplification and denoising. At the same time, eye movement correction is performed according to the eye movement correction information.

[0065] In one embodiment, for the above-mentioned signal preprocessing subunit, the signal preprocessing subunit performs eye movement correction according to the eye movement correction information, specifically in the following steps:

[0066] Signal reception and integration:

[0067] Receive the original eye movement signal (EOG) from the front-end acquisition subunit and the auxiliary eye movement correction information from the sensor subunit, the eye movement correction information including the acceleration and angular velocity data of the head;

[0068] Signal preprocessing:

[0069] Filtering and amplifying the original eye movement signal and the auxiliary eye movement correction information to remove noise and enhance signal strength;

[0070] State definition and initialization:

[0071] Define the state vector of the eye movement signal, which may include information such as the position and speed of the eyeball, and initialize the state vector and error covariance matrix;

[0072] Kalman filter iteration:

[0073] According to the state transfer matrix and the input control matrix, the eye movement signal state at the next moment is predicted. According to the observation matrix and the observation value, the Kalman gain is calculated. The predicted state is corrected using the Kalman gain and the observation value to obtain the posterior state estimate and update the error covariance matrix.

[0074] Corrected signal output:

[0075] The corrected eye movement signals are output to the data processing and analysis unit. These corrected signals can be used to more accurately analyze the user's eye movements, thereby supporting subsequent sleep monitoring, health assessment and other functions;

[0076] Assume that the state vector of the eye movement signal is defined as Among them, p t is the position of the eyeball, v t is the speed of the eyeball, and the state transfer matrix F is defined as Where Δt is the time interval, and the observation matrix H is defined as H =

[10] , which means that we only observe the position of the eyeball;

[0077] At a certain moment t, we receive the original eye movement signal zt from the front-end acquisition chip and the head movement information from the gyroscope. We first preprocess this information, then initialize the state vector and error covariance matrix. Next, we predict and update according to the iterative steps of the Kalman filter.

[0078] Prediction step: Use the state transfer matrix F and the state vector x at the previous moment t-1 To predict the current state vector

[0079] Update step: Use the observation matrix H and the observation value zt to calculate the Kalman gain Kt, and then use the Kalman gain and the observation value to correct the predicted state vector to obtain the posterior state estimate at the current moment At the same time, update the error covariance matrix Pt;

[0080] After multiple iterations, we can obtain a series of corrected eye movement signals, which can be used to more accurately analyze the user's eye movements.

[0081] In one embodiment, for the above-mentioned data processing and transmission unit, the data processing and transmission unit includes a signal separation subunit, a signal reconstruction and feature extraction subunit and a transmission subunit. The signal separation subunit realizes signal separation through a GPIO (general input output) module, converts an input signal into multiple output signals to meet the needs of different peripherals or functions. The signal reconstruction and feature extraction subunit uses the computing power and related algorithms of STM32F2 to reconstruct the signal and extract features. The reconstructed signal realizes signal denoising and smoothing. Feature extraction is used to extract key information or features in the signal. The transmission subunit is responsible for the wireless transmission of data, supports the BLE5.0 standard, and has low With the characteristics of power consumption and high transmission speed, it can upload data to the cloud server and receive control signals from the cloud. STM32F2 realizes signal input and separation by configuring the GPIO module. The separated signal is further processed by STM32F2 or output to other peripherals. STM32F2 uses its own computing power and related algorithms to reconstruct and extract features of the input signal. STM32F2 uploads the processed data to the cloud server through the BLE5.0 Bluetooth transmission subunit. After receiving the data, the cloud server processes, analyzes or makes decisions to generate control signals. The control signals are sent back to STM32F2 through the BLE5.0 Bluetooth transmission subunit to realize closed-loop control.

[0082] In one embodiment, for the above-mentioned sleep guidance and sleep monitoring unit, the sleep guidance and sleep monitoring unit includes a data processing and analysis subunit and an early warning execution subunit. The data processing and analysis subunit processes and analyzes the physiological signals collected by the signal acquisition unit, identifies apnea and abnormal blood oxygen saturation, and the early warning execution subunit accepts the personalized control plan provided by the cloud server, and activates the early warning function according to the personalized control plan and the analysis results of the data processing and analysis subunit. The early warning function includes vibration reminders and alarm sounds.

[0083] In one embodiment, for the above-mentioned cloud server, the cloud server includes a data analysis and processing unit, a personalized solution generation unit, a personalized service unit and a remote monitoring and management unit. The data analysis and processing unit is responsible for mining and analyzing the received physiological data, revealing the tourists' sleep status, health status and possible risks, and generating detailed sleep reports and data analysis results. The personalized solution generation unit generates a personalized sleep regulation solution based on the results of data analysis and processing. The personalized service unit sets personalized needs such as sleep goals and warning thresholds. The remote monitoring and management unit is responsible for providing and managing tourists' sleep data, analysis results and personalized regulation solutions.

[0084] In one embodiment, for the above-mentioned generation of a personalized sleep regulation plan, the personalized sleep regulation plan is generated in the following specific steps:

[0085] Data collection and preprocessing:

[0086] Collect tourists' electrooculogram, eye movement, respiration and blood oxygen physiological signals, evaluate tourists' altitude sickness according to their subjective feelings (such as headache, nausea, fatigue and other symptoms) and objective physiological indicators (such as the degree of decrease in blood oxygen saturation), and clean, denoise and standardize the collected data to ensure data quality and consistency;

[0087] Data analysis and mining:

[0088] Analyze the correlation between physiological data and the degree of altitude sickness and sleep quality. Based on the data analysis results, identify the possible health risks of tourists, such as severe altitude sickness and sleep disorders. According to the results of correlation analysis and risk identification, build a prediction model to predict the degree of altitude sickness and sleep quality changes that tourists may experience in the future.

[0089] Preset threshold settings:

[0090] Based on professional medical research and data verification, the normal range and abnormal thresholds of heart rate, respiratory rate and blood oxygen saturation physiological indicators are set. Different levels of altitude sickness thresholds are set according to the severity of altitude sickness. The thresholds of good and bad sleep quality are set according to the sleep duration and deep sleep ratio.

[0091] Personalized control plan generation:

[0092] According to tourists' physiological data, altitude sickness and sleep quality, combined with preset thresholds, a personalized control plan is formulated. The plan includes adjusting the sleeping environment (such as light, temperature, humidity), providing oxygen supply, recommending drug treatment or psychological counseling, etc. The control plan is dynamically adjusted and optimized according to tourists' real-time feedback and changes in physiological data;

[0093] Suppose a tourist experiences mild altitude sickness (such as headache and fatigue) and poor sleep quality (such as insufficient sleep duration and low proportion of deep sleep) while traveling in a plateau area. Based on the tourist's physiological data and symptom description, we can set the following preset thresholds:

[0094] Heart rate: Normal range 60-100 beats / min, abnormal threshold >120 beats / min or <40 beats / min.

[0095] Respiratory rate: normal range 12-20 times / min, abnormal threshold >30 times / min or <8 times / min.

[0096] Blood oxygen saturation: normal range 95%-100%, abnormal threshold <90%.

[0097] Altitude sickness thresholds: mild (headache, fatigue), moderate (nausea, vomiting), severe (confusion, difficulty breathing).

[0098] Sleep quality thresholds: high-quality sleep (deep sleep proportion > 25%, total sleep time > 6 hours), poor sleep (deep sleep proportion < 15%, total sleep time < 4 hours).

[0099] Based on the above preset thresholds, we can formulate the following personalized control plan for the tourist:

[0100] Adjust the sleeping environment, such as reducing light intensity and adjusting the room temperature to an appropriate range.

[0101] Provide supplemental oxygen, such as low-flow oxygen using a portable oxygen tank.

[0102] Drug treatment is recommended, such as taking drugs to relieve altitude sickness (follow doctor's advice).

[0103] Provide psychological counseling, such as providing precautions and coping methods for plateau travel, to reduce tourists' anxiety and tension.

[0104] At the same time, we need to continuously monitor the tourist's physiological data and symptom changes, and dynamically adjust and optimize the control plan based on actual conditions.

[0105] In one embodiment, for the above-mentioned data security module, the data security module includes a data encryption unit, an access control unit, a security audit and monitoring unit, a privacy compliance management unit, and a data backup and recovery unit. The data encryption unit is responsible for data encryption and decryption. The access control unit is responsible for managing user roles, permissions and identity authentication. The security audit and monitoring unit is responsible for monitoring system logs, detecting abnormal access and potential threats. The privacy compliance management unit ensures that system operations comply with privacy regulations and processes user privacy data. The data backup and recovery unit is responsible for regular data backup and disaster recovery plans. Before data storage, the data encryption unit encrypts the data and then passes the encrypted data to the data center for storage. The access control unit controls access to encrypted data and unencrypted data based on the user's role and permissions. When a user requests access to data, the access control unit first verifies the user's permissions and then allows or denies the access request. The security audit and monitoring unit monitors the system log in real time, including the access records of the access control unit and the data operation records of the data center. The data backup and recovery unit regularly copies data from the data center and stores it in a secure location.

[0106] The method of the plateau tourism intelligent eye mask system comprises the following steps:

[0107] Correctly wear the eye mask: The user needs to wear the smart eye mask on the eyes, ensuring that the eye mask fits tightly against the face to avoid light leakage or looseness. The signal acquisition unit detects the wearing status of the eye mask. If it detects that it is not worn correctly, it will vibrate to prompt the user to adjust it.

[0108] Receive and store personalized settings: Users send personalized settings to the sleep guidance and sleep monitoring units through the cloud server, including sleep goals, warning thresholds (such as apnea time, blood oxygen saturation lower limit, etc.);

[0109] Check sensor contact: Check the contact between the sensor and the user's skin to ensure the accuracy of data collection. If poor sensor contact is detected, the user will be prompted to adjust the wearing position of the eye mask through voice or vibration;

[0110] Start data collection: Users can start the signal collection unit through the mobile phone APP or the physical button on the eye mask to collect electrooculogram signals, eye movement signals, breathing signals and blood oxygen signals;

[0111] Data preprocessing: The collected signals are separated, reconstructed, and feature extracted to improve the accuracy and reliability of the data. The preprocessed data will be uploaded to the cloud server via BLE5.0 Bluetooth transmission;

[0112] Cloud processing and analysis: The cloud server processes and analyzes the received data to extract useful sleep information. The analysis results will be used for subsequent sleep monitoring and regulation;

[0113] Determine awake state: Determine whether the user is awake based on the collected physiological signals. If the user is awake, the sleep guidance program will be activated to help the user fall asleep quickly by playing soft music or sounds;

[0114] Check the wearing status again: After starting the sleep guidance program, check the wearing status of the eye mask again to ensure the sleep guidance effect;

[0115] Sleep apnea recognition: When the user falls asleep, the sleep guidance program stops and the sleep apnea recognition function is activated to determine whether the user has apnea by monitoring the breathing signal in real time;

[0116] Vibration and alarm: If the duration of apnea is detected to exceed the preset threshold (such as 5 seconds), the vibrator will be activated and an alarm will sound. The user can judge whether he / she has apnea based on the vibration and the alarm sound, and adjust his / her sleeping position or perform other necessary operations in time.

[0117] Respiration recovery judgment: After vibration and alarm, judge again whether the user's breathing is normal. If the breathing is normal, stop vibration and alarm. If the breathing is still abnormal, continue vibration and alarm until the user takes measures to solve the problem.

[0118] Stop monitoring and regulation: When the user wakes up or the system detects that the user has left the sleeping state, all monitoring and regulation functions are stopped.

[0119] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The plateau tourism intelligent eye mask system is characterized by: include: Signal acquisition unit: responsible for collecting electrooculogram, eye movement, respiration and blood oxygen physiological signals; Data processing and transmission unit: responsible for processing the physiological signals collected by the signal acquisition unit, including signal separation, reconstruction and feature extraction, uploading the processed data to the cloud server, and receiving control signals from the cloud server; Sleep guidance and sleep monitoring unit: responsible for receiving control signals from the cloud, monitoring tourists' sleep in real time, and activating corresponding early warning functions based on the monitoring results; Cloud server: responsible for receiving and storing processed data from the data processing and transmission unit, mining and analyzing the received processed data of multiple physiological parameters, revealing tourists' sleep status, health status and existing risks, customizing personalized control plans according to tourists' altitude sickness and sleep quality, and sending personalized control plans to the sleep guidance and sleep monitoring units through the data processing and transmission unit; Data Security and Privacy Protection Unit: Responsible for the security and privacy protection of business data during data storage, analysis and processing.

2. The plateau tourism intelligent eye mask system according to claim 1, characterized in that: The signal acquisition unit includes a front-end acquisition subunit, a sensor subunit and a signal preprocessing subunit. The front-end acquisition subunit is responsible for acquiring electrooculogram and eye movement signals. The front-end acquisition subunit transmits the acquired original electrooculogram and eye movement signals to the signal preprocessing subunit. The sensor subunit is responsible for acquiring respiratory signals, blood oxygen saturation signals and assisting in correcting eye movement signals. The sensor subunit transmits the acquired original respiratory signals to the signal preprocessing subunit, and at the same time, transmits the auxiliary eye movement correction information to the signal preprocessing subunit. The signal preprocessing subunit receives the original signals from the front-end acquisition subunit and the sensor subunit, performs filtering, amplification and denoising, and at the same time, performs eye movement correction according to the eye movement correction information.

3. The plateau tourism intelligent eye mask system according to claim 2, characterized in that: The signal preprocessing subunit performs eye movement correction according to the eye movement correction information, specifically in the following steps: Signal reception and integration: Receive the original eye movement signal from the front-end acquisition subunit and the auxiliary eye movement correction information from the sensor subunit; Signal preprocessing: Filtering and amplifying the original eye movement signal and the auxiliary eye movement correction information; State definition and initialization: Define the state vector of the eye movement signal, initialize the state vector and error covariance matrix; Kalman filter iteration: According to the state transfer matrix and the input control matrix, the eye movement signal state at the next moment is predicted. According to the observation matrix and the observation value, the Kalman gain is calculated. The predicted state is corrected using the Kalman gain and the observation value to obtain the posterior state estimate and update the error covariance matrix. Corrected signal output: The corrected eye movement signal is output to the data processing and analysis unit.

4. The plateau tourism intelligent eye mask system according to claim 1, characterized in that: The data processing and transmission unit includes a signal separation subunit, a signal reconstruction and feature extraction subunit and a transmission subunit. The signal separation subunit realizes signal separation through a GPIO module. The signal reconstruction and feature extraction subunit reconstructs the signal and extracts features. The reconstructed signal realizes signal denoising and smoothing. The feature extraction is used to extract key information or features in the signal. The transmission subunit is responsible for the wireless transmission of data.

5. The plateau tourism intelligent eye mask system according to claim 1, characterized in that: The sleep guidance and sleep monitoring unit includes a data processing and analysis subunit and an early warning execution subunit. The data processing and analysis subunit processes and analyzes the physiological signals collected by the signal acquisition unit to identify apnea and abnormal blood oxygen saturation. The early warning execution subunit accepts a personalized control plan provided by the cloud server, and activates an early warning function according to the personalized control plan and the analysis results of the data processing and analysis subunit. The early warning function includes a vibration reminder and an alarm sound.

6. The plateau tourism intelligent eye mask system according to claim 1, characterized in that: The cloud server includes a data analysis and processing unit, a personalized solution generation unit, a personalized service unit and a remote monitoring and management unit. The data analysis and processing unit is responsible for mining and analyzing the received physiological data, revealing the tourists' sleep status, health status and possible risks, and generating detailed sleep reports and data analysis results. The personalized solution generation unit generates a personalized sleep regulation solution based on the results of data analysis and processing. The personalized service unit sets personalized needs. The remote monitoring and management unit is responsible for providing and managing the tourists' sleep data, analysis results and personalized regulation solutions.

7. The plateau tourism intelligent eye mask system according to claim 6, characterized in that: The specific steps of generating a personalized sleep regulation plan are as follows: Data collection and preprocessing: Collect tourists' electrooculogram, eye movement, respiration and blood oxygen physiological signals, evaluate the degree of tourists' altitude sickness based on their subjective feelings and objective physiological indicators, and clean, denoise and standardize the collected data; Data analysis and mining: Analyze the correlation between physiological data and the degree of altitude sickness and sleep quality. Based on the data analysis results, identify the health risks of tourists. According to the results of correlation analysis and risk identification, build a prediction model to predict the degree of altitude sickness and sleep quality changes that tourists may experience in the future. Preset threshold settings: Based on professional medical research and data verification, the normal range and abnormal thresholds of heart rate, respiratory rate and blood oxygen saturation physiological indicators are set. Different levels of altitude sickness thresholds are set according to the severity of altitude sickness. The thresholds of good and bad sleep quality are set according to the sleep duration and deep sleep ratio. Personalized control plan generation: Based on tourists' physiological data, degree of altitude sickness and sleep quality, combined with preset thresholds, personalized control plans are formulated. According to tourists' real-time feedback and changes in physiological data, the control plans are dynamically adjusted and optimized.

8. The plateau tourism intelligent eye mask system according to claim 1, characterized in that: The data security module includes a data encryption unit, an access control unit, a security audit and monitoring unit, a privacy compliance management unit and a data backup and recovery unit. The data encryption unit is responsible for data encryption and decryption. The access control unit is responsible for managing user roles, permissions and identity authentication. The security audit and monitoring unit is responsible for monitoring system logs, detecting abnormal access and potential threats. The privacy compliance management unit ensures that system operations comply with privacy regulations and processes user privacy data. The data backup and recovery unit is responsible for regular data backup and disaster recovery plans. Before data storage, the data encryption unit encrypts the data and then passes the encrypted data to the data center for storage. The access control unit controls access to encrypted data and unencrypted data based on the user's role and permissions. When a user requests access to data, the access control unit first verifies the user's permissions and then allows or denies the access request. The security audit and monitoring unit monitors the system log in real time, including the access records of the access control unit and the data operation records of the data center. The data backup and recovery unit regularly copies data from the data center and stores it in a secure location.

9. The method of the plateau tourism intelligent eye mask system according to claim 1, characterized in that: The following steps are involved: Correctly wear the eye mask: The user needs to wear the smart eye mask on the eyes. The signal acquisition unit detects the wearing status of the eye mask. If it detects that it is not worn correctly, it will vibrate to prompt the user to adjust it. Receive and store personalized settings: Users send personalized settings to the sleep guidance and sleep monitoring units through the cloud server; Check sensor contact: Check the contact between the sensor and the user's skin. If poor sensor contact is detected, the user will be prompted to adjust the wearing position of the eye mask through voice or vibration; Start data collection: Start the signal acquisition unit to collect electrooculogram signals, eye movement signals, respiratory signals and blood oxygen signals; Data preprocessing: The collected signals are separated, reconstructed, and feature extracted, and the preprocessed data is uploaded to the cloud server; Cloud processing and analysis: The cloud server processes and analyzes the received data to extract useful sleep information; Determine awake state: Determine whether the user is awake based on the collected physiological signals. If the user is awake, the sleep guidance program will be activated to help the user fall asleep quickly by playing soft music or sounds; Check the wearing status again: After starting the sleep guidance program, check the wearing status of the eye mask again; Sleep apnea recognition: When the user falls asleep, the sleep guidance program stops and the sleep apnea recognition function is activated to determine whether the user has apnea by monitoring the breathing signal in real time; Vibration and alarm: If the duration of apnea is detected to exceed the preset threshold, the vibrator will be activated and an alarm will sound. The user can judge whether he / she has apnea based on the vibration and alarm sound and adjust his / her sleeping position in time. Respiration recovery judgment: After vibration and alarm, judge again whether the user's breathing is normal. If the breathing is normal, stop vibration and alarm. If the breathing is still abnormal, continue vibration and alarm until the user takes measures to solve the problem. Stop monitoring and regulation: When the user wakes up or the system detects that the user has left the sleeping state, all monitoring and regulation functions are stopped.

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