Remote monitoring method and system for lymphedema pressure treatment of patient at home

Abstract

The invention provides a remote monitoring method and system for lymphedema pressure treatment of a patient at home, and relates to the field of lymphedema pressure treatment. The remote monitoring system based on the lymphedema pressure treatment of the household patient comprises an intelligent tubular bandage, a multifunctional sensor module is embedded in the inner layer of the intelligent tubular bandage, and the intelligent tubular bandage comprises an ultrathin pressure sensor, a human body composition sensor, a skin texture monitor, a temperature sensor and a humidity sensor and is used for comprehensively monitoring various physiological parameters wound on limbs of the patient. Through the design of the multifunctional sensor module and the flexible circuit embedded in the intelligent tubular bandage, the accuracy and sensitivity of monitoring physiological parameters of a patient by the system are remarkably improved, the flexible circuit can be adaptively adjusted to adapt to the shape and movement of limbs of the patient, measurement errors caused by movement of the bandage or movement of the patient are reduced, and the measurement accuracy is improved. And the stability of data acquisition is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of lymphedema pressure therapy, and in particular to a remote monitoring method and system for lymphedema pressure therapy for patients at home. Background Art

[0002] The basic structure and principle of the remote monitoring system for pressure therapy of lymphedema in patients at home mainly include hardware devices such as ultra-thin pressure sensors embedded in tubular bandages, body composition sensors, and skin texture monitors. These sensors are installed in the therapeutic pressure bandages. When the patient wraps the bandage around the limbs, the sensors will collect the patient's pressure data, limb moisture, skin texture and other information in real time. These data are then transmitted to the cloud database for patients and medical staff to view and analyze through mobile phone applications. Medical staff can adjust the treatment plan based on these real-time data and communicate with patients to ensure the best treatment effect.

[0003] Although the system provides convenient remote monitoring and data transmission capabilities for patients at home, it still has some drawbacks. The accuracy and sensitivity of sensors and monitoring devices may be affected by patient usage and equipment wear, resulting in inaccurate data. Patients' increased dependence on the use of equipment may affect the overall effectiveness of the system due to improper operation or neglect of equipment maintenance. Summary of the invention

[0004] In response to the deficiencies in the prior art, the present invention provides a remote monitoring method and system for pressure therapy of lymphedema in patients at home, which solves the problem that the accuracy and sensitivity of sensors and monitoring equipment may be affected by patient usage and equipment wear, thereby leading to inaccurate data; and solves the problem that the overall effectiveness of the system may be affected by the increased dependence of patients on the use of equipment due to improper operation or neglect of equipment maintenance.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a remote monitoring system for pressure treatment of lymphedema in patients at home, comprising:

[0006] The smart tubular bandage has a multifunctional sensor module embedded in its inner layer, which includes an ultra-thin pressure sensor, a body composition sensor, a skin texture monitor, a temperature sensor, and a humidity sensor, which are used to comprehensively monitor various physiological parameters wrapped around the patient's limb;

[0007] The data processing unit integrates signal processing, data calibration, intelligent analysis and self-checking functions, and can process the data collected by sensors in real time and optimize the current monitoring results based on historical data;

[0008] Enhanced cloud database with intelligent data compression, redundant storage, and automatic detection and repair of abnormal data to ensure the security and integrity of data transmission and storage;

[0009] Mobile applications support simultaneous access from multiple terminals and have intelligent prompts, remote diagnosis, automatic data report generation and health guidance functions;

[0010] Auxiliary equipment maintenance module to monitor the status of system hardware and remind patients for maintenance or automatically schedule remote technical support.

[0011] Preferably, the multifunctional sensor module of the smart tubular bandage adopts a flexible circuit design, which can adaptively adjust according to the shape and movement of the limb to reduce measurement errors caused by bandage movement. The temperature sensor and humidity sensor integrated in the sensor module can monitor changes in the skin environment in real time, combined with pressure and skin texture data, to further improve sensitivity to changes in lymphedema.

[0012] Preferably, the intelligent analysis function in the data processing unit adopts a multi-dimensional data fusion algorithm to comprehensively analyze the data from different sensors to improve the accuracy and reliability of the monitoring results. The data processing unit has a self-learning function. By analyzing the patient data accumulated over a long period of time, it can continuously optimize the algorithm and adjust the monitoring strategy to adapt to individual differences. The cloud database has a data recovery function, which can automatically enable redundant storage for recovery when data is lost or damaged, thereby ensuring the continuous availability of data.

[0013] A method for remote monitoring of pressure therapy for lymphedema in a home patient comprises the following steps:

[0014] a. The smart tubular bandage is installed on the patient's limb to ensure that the multifunctional sensor module is in close contact with the patient's skin surface;

[0015] b. The sensor module automatically adjusts to the shape and movement of the patient's limbs through a flexible circuit design, ensuring the stability and accuracy of continuous monitoring;

[0016] c. The sensor module collects the patient's pressure, skin texture, temperature, humidity and body composition data in real time;

[0017] d. The data processing unit performs signal filtering and noise suppression on the collected raw data to ensure the validity of the data;

[0018] e. The data processing unit uses a multi-dimensional data fusion algorithm to conduct a comprehensive analysis of the data collected by different sensors to improve the accuracy and reliability of the monitoring results;

[0019] f. The data processing unit analyzes the patient's historical data, calibrates the current monitoring data, and continuously optimizes the monitoring algorithm through self-learning function;

[0020] g. The processed data is encrypted and transmitted to the enhanced cloud database, which automatically performs data compression and redundant storage, and has the function of automatically detecting and repairing abnormal data;

[0021] h. The system monitors abnormalities in the data in real time based on the analysis results. If an abnormality is found, it will immediately send an alert to the patient and medical staff through the mobile application and recommend appropriate treatment measures;

[0022] i. Medical staff can view patient data through mobile applications, remotely diagnose the patient's treatment status, and adjust the treatment plan when necessary;

[0023] j. The mobile application automatically generates health guidance and treatment recommendations based on the analysis results and the patient's historical data, and prompts the patient to follow them through voice or text;

[0024] k. The auxiliary equipment maintenance module regularly performs self-inspections on system hardware, predicts the service life of sensors and other hardware, and reminds patients to perform equipment maintenance or automatically arranges remote technical support;

[0025] l. The cloud database regularly backs up all data and automatically enables redundant storage for data recovery in the event of data loss or damage, ensuring data integrity and continuous availability.

[0026] Preferably, the adaptive adjustment of the flexible circuit in step b includes adjusting the circuit configuration in real time according to the feedback signal received by the sensor to minimize the measurement error caused by the patient's movement, and the real-time data acquisition in step c improves the sensitivity and accuracy to changes in skin texture, temperature and humidity through multi-frequency sampling technology.

[0027] Preferably, the multidimensional data fusion algorithm in step e adopts a weighted average algorithm to dynamically adjust the weight of each sensor data to optimize the overall analysis result. The self-learning function in step f automatically identifies the patient's unique physiological parameter change trend through multiple iterative analyses, and applies it in future monitoring to improve the accuracy of monitoring.

[0028] Preferably, the data transmission in step g is encrypted using blockchain technology to ensure the security and non-tamperability of the transmitted data, and the anomaly detection algorithm in step h adopts time series analysis method, which can predict possible abnormal situations in advance and issue early warnings.

[0029] Preferably, the remote diagnosis in step i includes automatically generating a detailed diagnostic report for medical staff to refer to and make adjustment suggestions, and the health guidance in step j includes automatically adjusting the guidance content based on the patient's daily activity data to ensure the personalization and practicality of the suggestions. The data processing unit includes a real-time dynamic adjustment function that can adjust the sensitivity of the sensor according to the patient's current physiological state, further reducing data inaccuracy caused by equipment wear or improper use.

[0030] The present invention provides a remote monitoring method and system for pressure therapy of lymphedema in patients at home. It has the following beneficial effects:

[0031] Through the multifunctional sensor module and flexible circuit design embedded in the intelligent tubular bandage, the present invention significantly improves the accuracy and sensitivity of the system in monitoring the patient's physiological parameters. The flexible circuit can adaptively adjust to the shape and movement of the patient's limbs, reduce the measurement error caused by bandage movement or patient movement, and ensure the stability of data collection. At the same time, the integrated temperature and humidity sensors can monitor the changes in the skin environment in real time, and combined with pressure and skin texture data, further enhance the system's sensitivity to changes in lymphedema.

[0032] The data processing unit uses a multi-dimensional data fusion algorithm and self-learning function. By comprehensively analyzing the data of different sensors, the accuracy and reliability of the monitoring results are improved. The system has intelligent analysis and self-checking functions, and can automatically calibrate and optimize the current monitoring algorithm based on historical data to adapt to individual differences in patients, thereby reducing data inaccuracies caused by equipment wear or improper operation. The system also ensures the security and immutability of data through enhanced cloud database and blockchain technology, and has anomaly detection and repair functions, further improving the overall effectiveness and stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention are described clearly and completely. 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.

[0035] like Figure 1As shown, an embodiment of the present invention provides a remote monitoring system for pressure treatment of lymphedema in patients at home, including a smart tubular bandage, an inner layer of which is embedded with a multifunctional sensor module, including an ultra-thin pressure sensor, a body composition sensor, a skin texture monitor, a temperature sensor and a humidity sensor, for comprehensively monitoring various physiological parameters wrapped around the patient's limbs. The multifunctional sensor module of the smart tubular bandage adopts a flexible circuit design, which can be adaptively adjusted according to the shape and movement of the limb to reduce measurement errors caused by bandage movement. The temperature sensor and humidity sensor integrated in the sensor module can monitor changes in the skin environment in real time, and combined with pressure and skin texture data, further improve the sensitivity to changes in lymphedema.

[0036] The data processing unit integrates signal processing, data calibration, intelligent analysis and self-test functions. It can process the data collected by the sensors in real time and optimize the current monitoring results based on historical data. The intelligent analysis function in the data processing unit adopts a multi-dimensional data fusion algorithm to comprehensively analyze the data from different sensors to improve the accuracy and reliability of the monitoring results. The data processing unit has a self-learning function. By analyzing the patient data accumulated over a long period of time, it can continuously optimize the algorithm and adjust the monitoring strategy to adapt to individual differences. The cloud database has a data recovery function, which can automatically enable redundant storage for recovery when the data is lost or damaged, to ensure the continuous availability of data.

[0037] The enhanced cloud database has intelligent data compression, redundant storage, and automatic detection and repair of abnormal data to ensure the security and integrity of data transmission and storage.

[0038] The mobile application supports simultaneous access from multiple terminals and has intelligent prompts, remote diagnosis, automatic data report generation and health guidance functions.

[0039] Auxiliary equipment maintenance module to monitor the status of system hardware and remind patients for maintenance or automatically schedule remote technical support.

[0040] A remote monitoring method for pressure therapy of lymphedema in patients at home, characterized in that it comprises the following steps:

[0041] a. The smart tubular bandage is installed on the patient's limb to ensure that the multifunctional sensor module is in close contact with the patient's skin surface.

[0042] b. The sensor module automatically adjusts to the shape and movement of the patient's limbs through a flexible circuit design to ensure the stability and accuracy of continuous monitoring. The flexible circuit adaptive adjustment includes real-time adjustment of the circuit configuration based on the feedback signal received by the sensor to minimize the measurement error caused by the patient's movement.

[0043] c. The sensor module collects the patient's pressure, skin texture, temperature, humidity and body composition data in real time. Real-time data collection uses multi-frequency sampling technology to improve the sensitivity and accuracy of changes in skin texture, temperature and humidity.

[0044] d. The data processing unit performs signal filtering and noise suppression on the collected raw data to ensure the validity of the data.

[0045] e. The data processing unit adopts a multi-dimensional data fusion algorithm to conduct a comprehensive analysis of the data collected by different sensors to improve the accuracy and reliability of the monitoring results. The multi-dimensional data fusion algorithm adopts a weighted average algorithm to dynamically adjust the weight of each sensor data to optimize the overall analysis results.

[0046] f. The data processing unit uses the self-learning function to analyze the patient's historical data, calibrate the current monitoring data, and continuously optimize the monitoring algorithm. The self-learning function automatically identifies the patient's unique physiological parameter change trends through multiple iterative analyses, and applies them in future monitoring to improve the accuracy of monitoring.

[0047] g. The processed data is encrypted and transmitted to the enhanced cloud database, which automatically performs data compression and redundant storage, and has the function of automatic detection and repair of abnormal data. Data transmission is encrypted using blockchain technology to ensure the security and non-tamperability of the transmitted data.

[0048] h. The system monitors anomalies in the data in real time based on the analysis results. If an anomaly is found, an alert is immediately sent to patients and medical staff through the mobile application, and appropriate treatment measures are recommended. The anomaly detection algorithm uses time series analysis to predict possible anomalies in advance and issue warnings.

[0049] i. Medical staff can view patient data through mobile applications, remotely diagnose the patient's treatment status, and adjust the treatment plan when necessary. Remote diagnosis includes automatically generating detailed diagnostic reports for medical staff to refer to and make adjustment suggestions.

[0050] j. The mobile application automatically generates health guidance and treatment recommendations based on the analysis results and the patient's historical data, and prompts the patient to follow them through voice or text. The health guidance includes automatic adjustment of the guidance content based on the patient's daily activity data to ensure the personalization and practicality of the recommendations. The data processing unit includes a real-time dynamic adjustment function that can adjust the sensitivity of the sensor according to the patient's current physiological state, further reducing data inaccuracies caused by equipment wear or improper use.

[0051] k. The auxiliary equipment maintenance module regularly performs self-inspections on system hardware, predicts the service life of sensors and other hardware, and reminds patients to perform equipment maintenance or automatically arranges remote technical support.

[0052] l. The cloud database regularly backs up all data and automatically enables redundant storage for data recovery in the event of data loss or damage, ensuring data integrity and continuous availability.

[0053] 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. A remote monitoring system for pressure therapy of lymphedema in patients at home, characterized in that: include: The smart tubular bandage has a multifunctional sensor module embedded in its inner layer, which includes an ultra-thin pressure sensor, a body composition sensor, a skin texture monitor, a temperature sensor, and a humidity sensor, which are used to comprehensively monitor various physiological parameters wrapped around the patient's limb; The data processing unit integrates signal processing, data calibration, intelligent analysis and self-checking functions, and can process the data collected by sensors in real time and optimize the current monitoring results based on historical data; Enhanced cloud database with intelligent data compression, redundant storage, and automatic detection and repair of abnormal data to ensure the security and integrity of data transmission and storage; Mobile applications support simultaneous access from multiple terminals and have intelligent prompts, remote diagnosis, automatic data report generation and health guidance functions; Auxiliary equipment maintenance module to monitor the status of system hardware and remind patients for maintenance or automatically schedule remote technical support.

2. A remote monitoring system for pressure therapy of lymphedema at home according to claim 1, characterized in that: The multifunctional sensor module of the smart tubular bandage adopts a flexible circuit design, which can adaptively adjust according to the shape and movement of the limb, reducing measurement errors caused by bandage movement. The temperature sensor and humidity sensor integrated in the sensor module can monitor changes in the skin environment in real time, and combined with pressure and skin texture data, further improve the sensitivity to changes in lymphedema.

3. A remote monitoring system for pressure therapy of lymphedema at home according to claim 1, characterized in that: The intelligent analysis function in the data processing unit adopts a multi-dimensional data fusion algorithm to comprehensively analyze the data from different sensors. The data processing unit has a self-learning function by analyzing the patient data accumulated over a long period of time. The cloud database has a data recovery function that can automatically enable redundant storage for recovery when data is lost or damaged.

4. A remote monitoring method for pressure therapy of lymphedema in patients at home, characterized in that: The following steps are involved: a. The smart tubular bandage is installed on the patient's limb to ensure that the multifunctional sensor module is in close contact with the patient's skin surface; b. The sensor module automatically adjusts to the shape and movement of the patient's limbs through a flexible circuit design, ensuring the stability and accuracy of continuous monitoring; c. The sensor module collects the patient's pressure, skin texture, temperature, humidity and body composition data in real time; d. The data processing unit performs signal filtering and noise suppression on the collected raw data to ensure the validity of the data; e. The data processing unit uses a multi-dimensional data fusion algorithm to conduct a comprehensive analysis of the data collected by different sensors to improve the accuracy and reliability of the monitoring results; f. The data processing unit analyzes the patient's historical data, calibrates the current monitoring data, and continuously optimizes the monitoring algorithm through self-learning function; g. The processed data is encrypted and transmitted to the enhanced cloud database, which automatically performs data compression and redundant storage, and has the function of automatically detecting and repairing abnormal data; h. The system monitors abnormalities in the data in real time based on the analysis results. If an abnormality is found, it will immediately send an alert to the patient and medical staff through the mobile application and recommend appropriate treatment measures; i. Medical staff can view patient data through mobile applications, remotely diagnose the patient's treatment status, and adjust the treatment plan if necessary; j. The mobile application automatically generates health guidance and treatment recommendations based on the analysis results and the patient's historical data, and prompts the patient to follow them through voice or text; k. The auxiliary equipment maintenance module regularly performs self-inspections on system hardware, predicts the service life of sensors and other hardware, and reminds patients to perform equipment maintenance or automatically arranges remote technical support; l. The cloud database regularly backs up all data and automatically enables redundant storage for data recovery in the event of data loss or damage, ensuring data integrity and continuous availability.

5. A remote monitoring method for pressure therapy of lymphedema in patients at home according to claim 4, characterized in that: The adaptive adjustment of the flexible circuit in step b includes real-time adjustment of the circuit configuration according to the feedback signal received by the sensor to minimize the measurement error caused by patient movement. The real-time data acquisition in step c improves the sensitivity and accuracy to changes in skin texture, temperature and humidity through multi-frequency sampling technology.

6. A remote monitoring method for pressure therapy of lymphedema in patients at home according to claim 4, characterized in that: The multidimensional data fusion algorithm in step e adopts a weighted average algorithm to dynamically adjust the weight of each sensor data to optimize the overall analysis result. The self-learning function in step f automatically identifies the patient's unique physiological parameter change trend through multiple iterative analyses, and applies it in future monitoring to improve the accuracy of monitoring.

7. A remote monitoring method for pressure therapy of lymphedema in patients at home according to claim 4, characterized in that: The data transmission in step g is encrypted using blockchain technology to ensure the security and non-tamperability of the transmitted data. The anomaly detection algorithm in step h adopts time series analysis method, which can predict possible abnormal situations in advance and issue early warnings.

8. A remote monitoring method for pressure therapy of lymphedema at home according to claim 4, characterized in that: The remote diagnosis in step i includes automatically generating a detailed diagnostic report for medical staff to refer to and make adjustment suggestions. The health guidance in step j includes automatically adjusting the guidance content based on the patient's daily activity data to ensure the personalization and practicality of the suggestions. The data processing unit includes a real-time dynamic adjustment function that can adjust the sensitivity of the sensor according to the patient's current physiological state, further reducing data inaccuracy caused by equipment wear or improper use.

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