Intelligent nursing system for postoperative rehabilitation of old people based on Internet of Things

Abstract

The invention discloses an intelligent nursing system for postoperative rehabilitation of old people based on Internet of Things, and relates to the technical field of medical nursing and Internet of Things. Comprising an Internet of Things sensing detection module used for collecting physiological data and environmental data of old people in real time and transmitting the data to a data processing and analyzing module through a wireless network; the data processing and analyzing module is used for receiving the transmitted data and processing, storing and analyzing the data in real time to form personalized health archives and rehabilitation assessment reports; the personalized nursing scheme generation module is used for formulating a personalized rehabilitation plan for the old people according to the rehabilitation evaluation report in combination with a big data analysis result; the remote monitoring and immediate intervention module is used for remotely monitoring the health condition and rehabilitation progress of the old people through an intelligent terminal; and the rehabilitation training module provides a VR / AR technology-based rehabilitation training system for old people. By integrating multiple advanced technologies, intelligence, individuation and precision of postoperative rehabilitation nursing of old people are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical care and the Internet of Things, and in particular relates to an intelligent nursing system for postoperative rehabilitation of the elderly based on the Internet of Things. Background Art

[0002] With the aging of the population, health problems of the elderly are becoming increasingly prominent, especially rehabilitation care after surgery has become an important issue that needs to be solved urgently. Traditional rehabilitation care has many shortcomings, such as limited medical and nursing resources, difficulty in quantifying and evaluating rehabilitation effects, and boring and lack of personalization in rehabilitation training. In addition, the physiological state of the elderly after surgery is complex and changeable, which places extremely high demands on the timeliness and accuracy of rehabilitation care.

[0003] The development of Internet of Things technology has provided a new solution for postoperative rehabilitation care for the elderly. Through Internet of Things technology, the physiological data, activity status and environmental information of the elderly can be collected in real time, providing comprehensive and accurate data support for medical staff, so as to formulate more scientific and personalized rehabilitation care plans.

[0004] However, most of the existing rehabilitation nursing systems based on the Internet of Things have problems such as insufficient data processing capabilities, lack of personalized nursing plan generation mechanism, and imperfect remote monitoring and immediate intervention functions. Therefore, there is an urgent need for a more advanced and complete intelligent nursing system for elderly people's postoperative rehabilitation based on the Internet of Things. Summary of the invention

[0005] The present invention aims to provide an intelligent nursing system for postoperative rehabilitation of the elderly based on the Internet of Things. The system integrates multiple advanced technologies to realize the intelligent, personalized and precise postoperative rehabilitation nursing of the elderly.

[0006] To solve the above technical problems, the present invention is achieved through the following technical solutions:

[0007] The present invention is an intelligent nursing system for elderly people's postoperative rehabilitation based on the Internet of Things, comprising:

[0008] The IoT sensor detection module is used to deploy a variety of sensors in the living environment of the elderly, collect the elderly's physiological data, activity status and environmental information in real time, and transmit the data to the data processing and analysis module through the wireless network;

[0009] The data processing and analysis module is used to receive the data transmitted by the IoT sensor detection module, perform real-time processing, storage and analysis, and form personalized health records and rehabilitation assessment reports;

[0010] The personalized care plan generation module develops personalized rehabilitation plans for the elderly based on the rehabilitation assessment report, combined with big data analysis results and medical knowledge base, including rehabilitation exercise plans, dietary recommendations, and psychological support;

[0011] Remote monitoring and immediate intervention module: medical staff and family members can remotely monitor the health status and rehabilitation progress of the elderly through smart terminals. The system has an abnormal warning function, and once an abnormal situation is found, the immediate intervention mechanism can be triggered immediately;

[0012] The rehabilitation training module provides the elderly with a rehabilitation training system based on VR / AR technology, providing them with a safe, comfortable rehabilitation environment and personalized rehabilitation training experience.

[0013] As a preferred technical solution of the present invention, the Internet of Things sensing detection module includes a heart rate sensor, a blood pressure sensor, a blood oxygen saturation sensor, a body temperature sensor, an activity monitoring sensor and an environmental parameter sensor. These sensors are connected to a data acquisition node via wired or wireless means, and the data acquisition node transmits the collected data to a cloud server or a local data center.

[0014] As a preferred technical solution of the present invention, the data acquisition nodes include but are not limited to smart wearable devices, smart mattresses and smart walkers.

[0015] As a preferred technical solution of the present invention, the data processing and analysis module includes:

[0016] The data receiving and storage module, data processing and cleaning module, intelligent analysis and evaluation module, and report generation and feedback module work together to process, analyze and evaluate the received data and generate personalized health records and rehabilitation assessment reports.

[0017] As a preferred technical solution of the present invention, the intelligent analysis and evaluation module includes:

[0018] A data cleaning and preprocessing module, which is used to remove noise, process missing values ​​and convert data on the received data;

[0019] A feature extraction and selection module, which is used to extract and select features that contribute most to the prediction target from the data;

[0020] A data partitioning module, wherein the data partitioning module is used to divide the data into a training set, a validation set, and a test set;

[0021] A model selection and training module, which is used to select a suitable machine learning algorithm and train the model on a training set;

[0022] A model evaluation and verification module, which is used to evaluate model performance on a verification set and perform overfitting and underfitting detection;

[0023] and a model optimization and adjustment module, wherein the model optimization and adjustment module is used to iteratively optimize the model according to the evaluation results.

[0024] As a preferred technical solution of the present invention, the personalized care plan generation module includes:

[0025] A plan-making tool for developing personalized care plans based on data analysis results;

[0026] Plan push function, push care plans to the elderly and their families through smart devices;

[0027] The program adjustment mechanism dynamically adjusts the care plan based on the elderly’s rehabilitation progress and feedback.

[0028] As a preferred technical solution of the present invention, it also includes a remote medical service module, which includes video calling and online consultation functions.

[0029] As a preferred technical solution of the present invention, the remote monitoring and immediate intervention module includes:

[0030] Real-time monitoring function, which can realize 24-hour real-time monitoring of the health status of the elderly through smart terminals;

[0031] Abnormal detection and early warning function: when the system detects abnormal physiological parameters or activity status of the elderly, it can automatically send out early warning signals;

[0032] Emergency contact function: once an emergency is discovered, the system can immediately notify the preset medical staff and family members and provide one-click rescue service.

[0033] As a preferred technical solution of the present invention, the rehabilitation training module includes:

[0034] VR / AR rehabilitation environment simulation, using virtual reality and augmented reality technology to provide an immersive rehabilitation training environment for the elderly;

[0035] Personalized training plan: develop a personalized training plan based on the specific rehabilitation needs and physical condition of the elderly;

[0036] Training progress tracking and feedback: real-time recording of the elderly’s training progress, and feedback and adjustments based on the training results.

[0037] As a preferred technical solution of the present invention, it also includes a smart medicine box equipped with a medication reminder module, which is connected to the cloud platform via a wireless module. The medication reminder module can receive medication instructions and remind the elderly to take medicine on time according to the doctor's prescription and the elderly's medication habits, and record the medication situation to ensure the safety and accuracy of medication.

[0038] The present invention has the following beneficial effects:

[0039] Improve rehabilitation effects: By real-time monitoring of the elderly’s physiological data and activity status, combined with big data analysis and personalized care plans, it is possible to accurately assess the elderly’s rehabilitation progress and adjust the rehabilitation plan in a timely manner, thereby improving rehabilitation effects.

[0040] Improve nursing efficiency: Use the Internet of Things and cloud computing technologies to realize automatic data collection, transmission and processing, reduce the workload of medical staff, and improve nursing efficiency.

[0041] Enhance patient experience: Provide an immersive rehabilitation training environment through VR / AR technology, making rehabilitation training more vivid and interesting, and improving the participation and satisfaction of the elderly.

[0042] Ensure medication safety: The smart medicine box can automatically remind the elderly to take medicine on time and record medication status, effectively avoiding problems such as missed or wrong medications, and ensuring medication safety.

[0043] Promote communication between doctors and patients: The telemedicine service module provides video calls and online consultation functions, which facilitates remote communication between the elderly and medical staff and timely solves problems encountered during the rehabilitation process.

[0044] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0046] Figure 1 It is a schematic diagram of the framework of the present invention;

[0047] Figure 2 is a schematic diagram of a data processing and analysis module in the present invention;

[0048] Figure 3 It is a schematic diagram of the intelligent analysis and evaluation module in the present invention. DETAILED DESCRIPTION

[0049] 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.

[0050] Embodiment 1

[0051] An intelligent nursing system for postoperative rehabilitation of the elderly based on the Internet of Things comprises: an Internet of Things sensing detection module, which is used to deploy a variety of sensors in the living environment of the elderly, collect the physiological data, activity status and environmental information of the elderly in real time, and transmit the data to a data processing and analysis module through a wireless network; a data processing and analysis module, which is used to receive the data transmitted by the Internet of Things sensing detection module, perform real-time processing, storage and analysis, and form a personalized health file and rehabilitation assessment report; a personalized nursing plan generation module, which formulates a personalized rehabilitation plan for the elderly according to the rehabilitation assessment report, combined with the big data analysis results and the medical knowledge base, including rehabilitation exercise plan, dietary advice, and psychological support; remote monitoring and The immediate intervention module uses smart terminals to allow medical staff and family members to remotely monitor the health status and rehabilitation progress of the elderly. The system has an abnormal warning function, and once an abnormal situation is found, the immediate intervention mechanism can be triggered immediately. The rehabilitation training module provides a rehabilitation training system based on VR / AR technology for the elderly, providing a safe and comfortable rehabilitation environment and personalized rehabilitation training experience for the elderly. The IoT sensor detection module includes heart rate sensors, blood pressure sensors, blood oxygen saturation sensors, body temperature sensors, activity monitoring sensors, and environmental parameter sensors. These sensors are connected to data collection nodes via wired or wireless means, and the data collection nodes transmit the collected data to cloud servers or local data centers. Data collection nodes include but are not limited to smart wearable devices, smart mattresses, and smart walkers.

[0052] In this embodiment, the system is mainly composed of the following key modules:

[0053] IoT sensor detection module: This module is responsible for deploying a variety of sensors in the living environment of the elderly, including but not limited to heart rate sensors, blood pressure sensors, blood oxygen saturation sensors, body temperature sensors, activity monitoring sensors, and environmental parameter sensors (such as temperature and humidity sensors). These sensors can collect physiological data (such as heart rate, blood pressure, blood oxygen saturation, body temperature), activity status (such as number of steps, sleep quality) and environmental information (such as indoor temperature and humidity) of the elderly in real time, and transmit these data to the data processing and analysis module securely and stably through wireless networks (such as Wi-Fi, Bluetooth, etc.). Its hardware composition: including various sensors, data acquisition nodes (such as smart bracelets, smart mattresses, smart walkers, etc.) and wireless communication modules.

[0054] Data processing and analysis module: This module receives data from the IoT sensor detection module for real-time processing, storage and analysis. Storage uses cloud servers or local data centers to achieve secure storage and backup of data. The analysis part uses big data analysis and artificial intelligence algorithms to conduct in-depth data mining to form personalized health records and rehabilitation assessment reports. It uses a distributed data processing architecture, combined with machine learning algorithms and medical knowledge bases, to efficiently and accurately process and analyze massive data.

[0055] Personalized care plan generation module: Based on rehabilitation assessment reports, big data analysis results and medical knowledge base, this module develops personalized rehabilitation plans for the elderly. These plans include but are not limited to rehabilitation exercise plans (such as exercise plans for joint range of motion and muscle strength), dietary recommendations (such as nutritionally balanced recipe recommendations), psychological support (such as psychological counseling, emotional management recommendations), etc. The rehabilitation plan is displayed to the elderly, medical staff and their families through smart terminals (such as mobile phone apps and tablets), and a plan adjustment function is provided to dynamically adjust according to the elderly's rehabilitation progress and feedback.

[0056] Remote monitoring and immediate intervention module: Through smart terminals, medical staff and family members can remotely monitor the health status and rehabilitation progress of the elderly. The system has an abnormal warning function that can automatically identify and warn of possible health risks for the elderly (such as abnormal heart rate, sudden increase in blood pressure, etc.). Once an abnormal situation is detected, the system can immediately trigger an immediate intervention mechanism, such as automatically sending an alarm to notify the preset medical staff and family members, or starting the emergency rescue process, and using encrypted communication technology and strict authority management strategies to ensure the security and reliability of the remote monitoring and immediate intervention process.

[0057] Rehabilitation training module: This module provides a rehabilitation training system based on VR / AR technology for the elderly. Through virtual reality (VR) and augmented reality (AR) technology, a safe and comfortable rehabilitation environment is created for the elderly, and a personalized rehabilitation training experience is provided. These training contents can be customized according to the rehabilitation needs and physical conditions of the elderly, including balance training, gait training, cognitive function training, etc. VR / AR technology can stimulate the elderly's interest in participation and improve the training effect; at the same time, by simulating real scenes, it helps the elderly better adapt to the actual living environment.

[0058] The intelligent nursing system for postoperative rehabilitation of the elderly in this embodiment realizes the intelligent, personalized and precise postoperative rehabilitation nursing of the elderly by integrating advanced technologies such as the Internet of Things, big data, artificial intelligence, VR / AR, etc. The system not only improves the rehabilitation effect and nursing efficiency, but also enhances the rehabilitation experience and satisfaction of the elderly. At the same time, the safety and health of the elderly are guaranteed through remote monitoring and immediate intervention functions.

[0059] Embodiment 2

[0060] Based on the first embodiment, the difference of this embodiment is that:

[0061] The data processing and analysis module includes: data receiving and storage module, data processing and cleaning module, intelligent analysis and evaluation module and report generation and feedback module. These modules work together to process, analyze and evaluate the received data, and generate personalized health records and rehabilitation assessment reports. The intelligent analysis and evaluation module includes: data cleaning and preprocessing module, which is used to remove noise, process missing values ​​and convert data for the received data; feature extraction and selection module, which is used to extract and select features that contribute most to the prediction target from the data; data partitioning module, which is used to divide the data into training set, validation set and test set; model selection and training module, which is used to select appropriate machine learning algorithms and train models on the training set; model evaluation and verification module, which is used to evaluate model performance on the validation set and perform overfitting and underfitting detection; and model optimization and adjustment module, which is used to iteratively optimize the model according to the evaluation results.

[0062] Based on the first embodiment, this embodiment further refines the internal structure and workflow of the data processing and analysis module. By introducing a more refined data processing and intelligent analysis mechanism, this embodiment aims to improve the accuracy and efficiency of data processing, as well as the personalization and accuracy of rehabilitation assessment reports.

[0063] The data processing and analysis module consists of the following submodules, which work together to perform comprehensive and in-depth processing, analysis and evaluation of the received data:

[0064] Data receiving and storage module:

[0065] Responsible for receiving data from the IoT sensor detection module and performing preliminary verification and format conversion.

[0066] The verified data is stored in a secure and reliable database for subsequent processing and analysis.

[0067] Data processing and cleaning module:

[0068] Data cleaning and preprocessing module: remove noise, process missing values ​​and convert data for received data to ensure data integrity and consistency. Noise removal includes filtering, de-jittering and other technologies; missing value processing may use interpolation, deletion or marking methods; data conversion involves standardization and normalization of data formats.

[0069] Feature extraction and selection module: Extract and select the features that contribute most to the prediction target (such as rehabilitation effect, health risk) from the cleaned data. These features may include the changing trend of physiological indicators, the statistical characteristics of activity status, the correlation of environmental parameters, etc.

[0070] Intelligent analysis and evaluation module:

[0071] Data partitioning module: divides the processed data into training set, validation set and test set to provide data support for model training and evaluation;

[0072] Model selection and training module: According to the task requirements and data characteristics, select the appropriate machine learning algorithm (such as decision tree, random forest, neural network, etc.), and train the model on the training set. The training process may involve steps such as hyperparameter tuning;

[0073] Model evaluation and verification module: Evaluate model performance on the verification set, including accuracy, recall, F1 score and other indicators. At the same time, perform overfitting and underfitting detection to ensure the generalization ability of the model;

[0074] Model optimization and adjustment module: Iteratively optimize the model based on the evaluation results, including adjusting the model structure, changing the algorithm, optimizing hyperparameters, etc. The optimized model will be re-evaluated on the validation set until satisfactory performance is achieved;

[0075] Report generation and feedback module:

[0076] Based on the results of intelligent analysis and evaluation, a personalized health record and rehabilitation assessment report are generated. The report may include analysis of the elderly's physiological condition, rehabilitation progress assessment, potential health risk warnings, and personalized rehabilitation suggestions. The report is pushed to medical staff, family members, and the elderly themselves through smart terminals so that they can understand the rehabilitation status and adjust the rehabilitation plan in a timely manner.

[0077] Through the detailed implementation of the data processing and analysis module in this embodiment, the system can process and analyze the health data of the elderly more accurately and efficiently, and generate more personalized and accurate rehabilitation assessment reports. This not only improves the scientificity and effectiveness of rehabilitation care, but also enhances the ability of medical staff and family members to monitor the health status of the elderly. At the same time, by continuously optimizing model performance and improving the accuracy of data processing, the system can continue to provide better quality rehabilitation care services for the elderly.

[0078] Embodiment 3

[0079] Based on the first embodiment, the difference of this embodiment is that:

[0080] The personalized care plan generation module includes: a plan-making tool, which is used to formulate personalized care plans based on data analysis results; a plan push function, which pushes care plans to the elderly and their families through smart devices; and a plan adjustment mechanism, which dynamically adjusts the care plan based on the elderly's rehabilitation progress and feedback.

[0081] The remote monitoring and immediate intervention module includes: real-time monitoring function, which enables 24-hour real-time monitoring of the health status of the elderly through smart terminals; abnormal detection and early warning function, which can automatically issue an early warning signal when the system detects abnormalities in the physiological parameters or activity status of the elderly; emergency contact function, once an emergency is discovered, the system can immediately notify the preset medical staff and family members, and provide one-click rescue service.

[0082] The rehabilitation training modules include: VR / AR rehabilitation environment simulation, using virtual reality and augmented reality technology to provide an immersive rehabilitation training environment for the elderly; personalized training plans, formulating personalized training plans based on the specific rehabilitation needs and physical conditions of the elderly; training progress tracking and feedback, real-time recording of the elderly's training progress, and providing feedback and adjustments based on the training results.

[0083] Based on the first embodiment, this embodiment further expands the functions of the system, focusing on strengthening the generation of personalized care plans, remote monitoring and immediate intervention capabilities, and introducing advanced rehabilitation training modules. These extensions are intended to provide more comprehensive, detailed and efficient rehabilitation care services to promote rapid recovery and health management of the elderly.

[0084] Among them, the personalized care plan generation module: Plan formulation tool: integrates advanced algorithms and expert knowledge bases, and automatically or semi-automatically formulates personalized care plans based on the health data, rehabilitation progress, and living habits of the elderly provided by the data analysis module. The content of the plan covers multiple aspects such as daily care, dietary guidance, and psychological support. Plan push function: Push personalized care plans to the elderly and their families through smart devices (such as smartphones, tablets, or smart wearable devices) with a friendly interface and notification method. Ensure timely communication and effective receipt of information. Plan adjustment mechanism: Establish a flexible feedback mechanism to allow the elderly, their families, and medical staff to submit feedback through the system interface based on the progress of rehabilitation and actual conditions. Based on these feedbacks and combined with the latest data analysis results, the system dynamically adjusts the care plan to ensure the continued effectiveness and personalization of care services.

[0085] Remote monitoring and immediate intervention module:

[0086] Real-time monitoring function: Using the Internet of Things technology, the health status of the elderly can be monitored in real time 24 hours a day through smart terminals (such as smart wearable devices, smart home devices, etc.). The monitoring content includes but is not limited to physiological parameters (such as heart rate, blood pressure, blood sugar, etc.), activity status (such as gait, sleep quality, etc.) and environmental changes (such as indoor temperature, humidity, etc.).

[0087] Abnormal detection and early warning function: Integrate advanced abnormal detection algorithms to analyze monitoring data in real time. Once abnormal physiological parameters or activity status of the elderly are detected, the system automatically sends out an early warning signal and notifies the preset medical staff and family members through smart devices, text messages, phone calls, etc.

[0088] Emergency contact function: When an emergency is discovered, the system can immediately start the emergency contact process, automatically dial the preset emergency contact number, and provide one-click emergency service. At the same time, the system can record the time, location and initial handling of the emergency incident to provide a reference for subsequent processing.

[0089] Rehabilitation training module:

[0090] VR / AR rehabilitation environment simulation: Use virtual reality (VR) and augmented reality (AR) technologies to create an immersive rehabilitation training environment for the elderly. By simulating real rehabilitation scenes and training movements, the participation and training effect of the elderly can be improved. At the same time, VR / AR technology can also provide rich visual, auditory and tactile feedback to enhance the training experience. Personalized training plan: According to the specific rehabilitation needs and physical condition of the elderly, combined with the advice of rehabilitation experts, a personalized training plan is formulated. The plan content covers training goals, training content, training intensity and training time to ensure the scientificity and effectiveness of the training. Training progress tracking and feedback: The training progress and training effect of the elderly are recorded in real time through smart devices. The system analyzes and evaluates the collected data and provides training feedback and suggestions for the elderly. At the same time, medical staff and family members can also view the training status of the elderly through the system interface to better understand their rehabilitation progress and make necessary interventions.

[0091] Embodiment 4

[0092] Based on the first embodiment, in other optional embodiments, the module further includes:

[0093] Telemedicine service module, the telemedicine service module includes video call and online consultation functions.

[0094] It also includes a smart medicine box equipped with a medication reminder module. The medicine box is connected to the cloud platform via a wireless module. The medication reminder module can receive medication instructions and remind the elderly to take medication on time based on the doctor's prescription and the elderly's medication habits, and record medication status to ensure the safety and accuracy of medication.

[0095] Based on the first embodiment, this embodiment further integrates the remote medical service module and the medication reminder function of the smart medicine box, aiming to improve the medical service experience of the elderly and the convenience and safety of medication management through scientific and technological means.

[0096] Telemedicine service module:

[0097] Video call function: Provides high-definition and stable video call services, allowing the elderly to communicate with doctors face to face at home. This not only facilitates the elderly's follow-up visits and consultations, but also reduces their troubles caused by travel inconvenience.

[0098] Online consultation function: The elderly or their family members can submit descriptions of their conditions and questions through the system interface, and online doctors will answer and provide guidance. This function supports multiple communication methods such as text, image, and voice to ensure accurate communication of information and timely feedback.

[0099] Smart medicine box and medication reminder module:

[0100] Smart medicine box design: The smart medicine box adopts a humanized design and is easy for the elderly to operate. There are multiple compartments inside the medicine box to store different types of medicines as needed. The surface of the medicine box is equipped with a clear display and simple operation buttons, which makes it convenient for the elderly to view medication information and operate.

[0101] Wireless connection and cloud platform: The smart medicine box maintains real-time connection with the cloud platform through the built-in wireless module. The cloud platform is responsible for receiving the doctor's prescription information, the elderly's medication habits and other data, and generates medication instructions based on this and sends them to the smart medicine box.

[0102] Medication reminder and record: The medication reminder module will remind the elderly to take medication on time at the designated time through sound, vibration or screen display according to the medication instructions received. At the same time, the medicine box also has a medication record function, which automatically records the elderly's medication situation (such as medication time, medication amount, etc.), and can synchronize the recorded data to the cloud platform for medical staff and family members to view.

[0103] Medication safety and accuracy: The smart medicine box's medication reminder and recording functions can effectively avoid medication errors caused by elderly people forgetting or confusing medications. At the same time, the cloud platform's data analysis capabilities can also help medical staff identify potential medication risks in a timely manner and provide safer and more accurate medication guidance for the elderly.

[0104] The remote medical service module and the medication reminder function of the smart medicine box in this embodiment further enrich the service content of the system, improve the convenience and safety of the medical service experience and medication management during the rehabilitation process of the elderly. The introduction of these functions not only helps the rapid recovery and health management of the elderly, but also reduces the burden on medical staff and family members.

[0105] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0106] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent nursing system for elderly people's postoperative rehabilitation based on the Internet of Things, characterized in that: include: The IoT sensor detection module is used to deploy a variety of sensors in the living environment of the elderly, collect the elderly's physiological data, activity status and environmental information in real time, and transmit the data to the data processing and analysis module through the wireless network; The data processing and analysis module is used to receive the data transmitted by the IoT sensor detection module, perform real-time processing, storage and analysis, and form personalized health records and rehabilitation assessment reports; The personalized care plan generation module develops personalized rehabilitation plans for the elderly based on the rehabilitation assessment report, combined with big data analysis results and medical knowledge base, including rehabilitation exercise plans, dietary recommendations, and psychological support; Remote monitoring and immediate intervention module: medical staff and family members can remotely monitor the health status and rehabilitation progress of the elderly through smart terminals. The system has an abnormal early warning function, and once an abnormal situation is found, the immediate intervention mechanism can be triggered immediately; The rehabilitation training module provides a rehabilitation training system based on VR / AR technology for the elderly.

2. According to the IoT-based intelligent nursing system for elderly people after surgery, the system is characterized in that: The IoT sensing detection module includes a heart rate sensor, a blood pressure sensor, a blood oxygen saturation sensor, a body temperature sensor, an activity monitoring sensor, and an environmental parameter sensor. These sensors are connected to a data acquisition node via wired or wireless means, and the data acquisition node transmits the collected data to a cloud server or a local data center.

3. According to the IoT-based intelligent nursing system for elderly people's postoperative rehabilitation, the system is characterized by: The data collection nodes include but are not limited to smart wearable devices, smart mattresses and smart walkers.

4. According to the IoT-based intelligent nursing system for elderly people's postoperative rehabilitation, the system is characterized by: The data processing and analysis module includes: The data receiving and storage module, data processing and cleaning module, intelligent analysis and evaluation module, and report generation and feedback module work together to process, analyze and evaluate the received data and generate personalized health records and rehabilitation assessment reports.

5. According to the IoT-based intelligent nursing system for elderly people's postoperative rehabilitation, the system is characterized in that: The intelligent analysis and evaluation module includes: A data cleaning and preprocessing module, which is used to remove noise, process missing values ​​and convert data on the received data; A feature extraction and selection module, which is used to extract and select features that contribute most to the prediction target from the data; A data partitioning module, wherein the data partitioning module is used to divide the data into a training set, a validation set, and a test set; A model selection and training module, which is used to select a suitable machine learning algorithm and train the model on a training set; A model evaluation and verification module, which is used to evaluate model performance on a verification set and perform overfitting and underfitting detection; and a model optimization and adjustment module, wherein the model optimization and adjustment module is used to iteratively optimize the model according to the evaluation results.

6. According to the IoT-based intelligent nursing system for elderly people's postoperative rehabilitation, the system is characterized by: The personalized nursing plan generation module includes: A plan-making tool for developing personalized care plans based on data analysis results; Plan push function, push care plans to the elderly and their families through smart devices; The program adjustment mechanism dynamically adjusts the care plan based on the elderly’s rehabilitation progress and feedback.

7. According to the IoT-based intelligent nursing system for elderly people's postoperative rehabilitation, the system is characterized by: It also includes a remote medical service module, which includes video call and online consultation functions.

8. According to the IoT-based intelligent nursing system for elderly people's postoperative rehabilitation, the system is characterized by: The remote monitoring and immediate intervention module includes: Real-time monitoring function, which can realize 24-hour real-time monitoring of the health status of the elderly through smart terminals; Abnormal detection and early warning function: when the system detects abnormal physiological parameters or activity status of the elderly, it can automatically send out early warning signals; Emergency contact function: once an emergency is discovered, the system can immediately notify the preset medical staff and family members and provide one-click rescue service.

9. The intelligent nursing system for elderly people's postoperative rehabilitation based on the Internet of Things according to claim 1 is characterized in that: The rehabilitation training module includes: VR / AR rehabilitation environment simulation, using virtual reality and augmented reality technology to provide an immersive rehabilitation training environment for the elderly; Personalized training plan: develop a personalized training plan based on the specific rehabilitation needs and physical condition of the elderly; Training progress tracking and feedback: real-time recording of the elderly’s training progress, and feedback and adjustments based on the training results.

10. The intelligent nursing system for elderly people's postoperative rehabilitation based on the Internet of Things according to claim 1 is characterized in that: It also includes a smart medicine box equipped with a medication reminder module, which is connected to the cloud platform via a wireless module. The medication reminder module can receive medication instructions and remind the elderly to take medication on time based on the doctor's prescription and the elderly's medication habits, and record medication status to ensure the safety and accuracy of medication.

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