Method and device for analyzing physical states of old people by detecting air components in bedroom

Abstract

The invention discloses a method and device for analyzing the physical state of old people by detecting air components in a bedroom, and the method comprises the following steps: installing a sensor array in an indoor environment where the old people live or move frequently, and detecting VOC components in the air in real time; the sensor collects data once every 1-5 minutes and transmits the data to the central processing unit for processing; after the central processing unit receives the sensor data, data correction is carried out, denoising processing is carried out on sensor output signals, and interference caused by environment changes is eliminated; the method has the beneficial effects that the data accuracy is optimized by combining environment regulation and sensor acquisition; the comprehensive capability of health monitoring is improved by adopting various sensor arrays; a machine learning algorithm is utilized to intelligently evaluate the health condition, and personalized health management is realized through cloud data storage and remote feedback; due to the improvements, the system has high accuracy, sensitivity and real-time performance in health monitoring of the old people.

Description

Technical Field

[0001] The present invention belongs to the technical field of health monitoring, and particularly relates to a method and a device for analyzing the physical state of the elderly by detecting the air components in the bedroom. Background Art

[0002] In recent years, with the acceleration of the social aging process, the health problems of the elderly have become an important topic of global concern; traditional health monitoring means mostly rely on hospital diagnosis, physical examination and wearable devices; however, these methods often have limitations such as high cost, low detection frequency and dependence on active participation, and it is difficult to meet the long-term and real-time health monitoring needs of the elderly, especially the elderly living alone or the disabled elderly; therefore, it is particularly important to develop a low-cost, non-invasive and real-time health monitoring method.

[0003] In the human metabolic process, a variety of volatile organic compounds (VOCs) and other gas components will be released, and these substances can enter the air through breathing, sweating or skin volatilization; research shows that different diseases will lead to changes in human metabolic characteristics, thus generating specific gas markers; for example:

[0004] Diabetes: The exhaled gas of patients will contain a higher concentration of acetone;

[0005] Abnormal liver function: It is often accompanied by an increase in the concentration of ammonia and dimethyl sulfide in the air;

[0006] Infection or inflammation: It may cause abnormal changes in the concentration of hydrogen sulfide or ammonia;

[0007] Lung diseases: It will affect the concentration of nitrogen oxide or nitric oxide in breathing;

[0008] Based on the non-invasive health monitoring technology of air component analysis, certain progress has been made in recent years; for example, VOC gas sensor technology has been widely used in the field of air quality monitoring and also shows potential in medical gas detection; however, these technologies still face the following problems and disadvantages in practical applications:

[0009] Insufficient gas detection sensitivity: The existing gas sensors have low detection sensitivity to low-concentration VOCs and are difficult to capture the trace gas signals related to early disease risks;

[0010] Multi-gas cross-interference: There are various gas components in the air, and there may be cross-interference between them, resulting in inaccurate detection results; in addition, environmental factors such as temperature and humidity will also affect the sensor performance;

[0011] Limited real-time analysis capabilities: The analysis speed of some existing devices is slow, making it difficult to achieve real-time health monitoring. In addition, due to limited data processing capabilities, traditional devices are difficult to improve the detection accuracy by comprehensively analyzing gas patterns.

[0012] High cost and large device volume: Although some high-performance detection devices such as gas chromatographs and mass spectrometers have high sensitivity, they are expensive and bulky, making it difficult to promote their use in the home environment.

[0013] Lack of systematic solutions: Existing technologies mostly focus on the detection of single gases, lacking a comprehensive health assessment system that combines multiple gas components and data models, and unable to comprehensively reflect the health status of the human body. Summary of the Invention

[0014] The purpose of the present invention is to provide a method and device for analyzing the physical state of the elderly by detecting the air components in the bedroom. By detecting the VOC or other organic compound components in the air, accurately evaluate the physical condition of the elderly, solve the technical bottleneck, achieve real-time and non-invasive health monitoring, and improve the level of health management for the elderly.

[0015] To achieve the above object, the present invention provides the following technical solution: A method for analyzing the physical state of the elderly by detecting the air components in the bedroom, including the following steps:

[0016] Install a sensor array in the indoor environment where the elderly usually live or move, and detect the VOC components in the air in real time.

[0017] The sensor collects data every 1-5 minutes and transmits the data to the central processing unit for processing.

[0018] After receiving the sensor data, the central processing unit performs data correction, denoises the sensor output signal, and eliminates the interference caused by environmental changes, such as temperature and humidity changes.

[0019] The corrected data evaluates the change trend of the current indoor air components through the built-in algorithm model, and judges the physical state of the elderly.

[0020] The system analyzes the correlation between the VOC concentration in the air and the health status of the elderly based on the trained machine learning model, and judges whether there is a health abnormality.

[0021] If a health abnormality is detected, such as an abnormal increase in acetone concentration may indicate diabetes, the system sends an alarm message to the guardian or medical staff through the communication module.

[0022] The guardian views the health report of the elderly through a mobile device and intervenes according to the prompt.

[0023] The system automatically adjusts the indoor air quality according to environmental conditions, such as starting an air purifier or adjusting the ventilation system;

[0024] The sensor continuously self-corrects through a feedback mechanism to ensure the reliability of the monitoring data.

[0025] As a preferred technical solution of the present invention, the central processing unit includes a microprocessor, a data storage unit and a communication module, and performs real-time processing, storage and transmission of data.

[0026] As a preferred technical solution of the present invention, the communication module transmits the health assessment results and warning information to mobile phones, tablet computer terminal devices.

[0027] As a preferred technical solution of the present invention, the machine learning model is trained with a large amount of clinical data.

[0028] The present invention also discloses a device for analyzing the physical state of the elderly by detecting the air components in the bedroom, including

[0029] An air component collection device, which uses a highly sensitive sensor array and can detect VOCs and other organic compound components in indoor air; the sensor array is composed of multiple different types of sensors, and each sensor has strong selectivity and high sensitivity to specific chemical components; for example, metal oxide semiconductor sensors MOS, electrochemical sensors or optical sensors are used to detect volatile organic compounds such as formaldehyde, ethanol, and acetone respectively, and each sensor is connected to the central processing unit through a circuit to monitor the chemical components in the air in real time;

[0030] A data collection and processing module, which converts the detected VOC concentration data into digital signals through sensors and transmits them to the central processing unit for further processing. The central processing unit includes a microprocessor, a data storage unit and a communication module, and can perform real-time processing, storage and transmission of data. The microprocessor is responsible for correcting and denoising the data collected by different sensors to ensure the accuracy and reliability of the data;

[0031] An air quality adjustment and environmental interference elimination module, which controls the ventilation, humidity and temperature in the room, reduces the interference of the environment on the sensor detection results, and is adjusted through an intelligent fan, a humidifier and an air conditioning system to stabilize the VOC components in the air and ensure the reliability of the measurement results. By collecting environmental parameters such as temperature and humidity and combining them with sensor data for compensation, the impact of environmental changes on the monitoring results is reduced;

[0032] Data analysis and health assessment algorithm module, which uses machine learning-based algorithms to analyze the collected air composition data and extract features related to the health status of the elderly; by establishing a model, different VOC concentrations are associated with the diseases or health status of the elderly, such as diabetes, respiratory diseases, and cardiovascular diseases, so as to realize the real-time assessment of the physical condition of the elderly. This model needs to be trained with a large amount of clinical data to improve the accuracy of the algorithm;

[0033] Real-time monitoring and feedback system, which can send alerts to guardians or medical staff in a timely manner when the health status of the elderly changes; the system transmits the health assessment results and warning information to terminal devices such as mobile phones and tablets through a wireless communication module to ensure that guardians can obtain the health information of the elderly in a timely manner; the system also supports cloud storage and analysis, which is convenient for the accumulation and analysis of long-term health data;

[0034] Compared with the prior art, the beneficial effects of the present invention are:

[0035] By combining environmental regulation and sensor collection, the data accuracy is optimized; a variety of sensor arrays are used to improve the comprehensive ability of health monitoring; machine learning algorithms are used to intelligently evaluate the health status, and personalized health management is realized through cloud data storage and remote feedback; these improvements make the present invention have high accuracy, sensitivity and real-time performance in the health monitoring of the elderly, can provide a more comprehensive and accurate health assessment and warning for the elderly, and have high market application value; help guardians or medical staff make quick responses and provide strong support for the health management of the elderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is the method flowchart of the present invention;

[0037] Figure 2 is the schematic diagram of the device of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] Embodiment 1

[0040] Please refer to Figure 2 , which is the first embodiment of the present invention. This embodiment provides a device for analyzing the physical state of the elderly by detecting the air composition in the bedroom, including:

[0041] Air Composition Sampling Module: The system first uses a sensor array installed indoors to detect the VOC composition in the air in real time. These sensors can detect various volatile organic compounds (such as formaldehyde, ethanol, acetone, etc.) and other organic compounds, and the concentrations of these compounds can reflect the health status of the elderly. For example, diabetic patients may release more acetone in their exhaled breath, while patients with some respiratory diseases may release specific organic compounds. The sensors automatically collect the composition data in the air at regular intervals (such as every minute).

[0042] Data Transmission and Processing Module: The data collected by the sensors is transmitted to the central processing unit (central control system) in real time through the wireless communication module. This system uses a microprocessor to process the data in real time. First, the raw data is corrected and denoised to eliminate the influence of environmental factors such as temperature and humidity on the data. The corrected data is analyzed through algorithms, and the system will establish a correlation between different VOC concentrations and the health status of the elderly.

[0043] Health Assessment Module: The health assessment module is based on a trained machine learning model and uses the processed VOC concentration information to judge the health status of the elderly. For example, by analyzing the concentration changes of gases such as acetone, aldehydes, and alcohols, the system can identify potential health problems, such as diabetes, respiratory diseases, liver diseases, cardiovascular problems, etc. If the concentration of certain organic compounds is monitored to exceed a certain threshold, the system will judge that the elderly may have health problems and generate a corresponding health assessment report.

[0044] Environmental Regulation and Interference Elimination Module: To ensure the accuracy of data collection, this system integrates an environmental regulation module, which reduces the influence of environmental factors on sensor detection by controlling indoor ventilation, humidity, temperature, etc. For example, the system can automatically adjust the air conditioner, humidifier or fan to ensure the stability of the air composition. In addition, the system performs compensation processing in real time according to the environmental data collected by the sensors to further ensure the accuracy of the monitoring data.

[0045] Feedback and Alarm Module: Once the system detects an abnormal health status of the elderly (such as an abnormal increase in the concentration of certain volatile organic compounds), the system will immediately send an alarm message to the guardian or medical staff through the wireless communication module to remind them to pay attention to the health status of the elderly. The guardian can view the real-time health assessment results through a mobile application or a computer terminal. If the health status is relatively serious, the system can be set to automatically call an emergency phone or notify the relevant medical service provider.

[0046] Real-time Monitoring and Health Data Storage: This system has a continuous monitoring function. It not only evaluates the health status of the elderly in real time but also stores historical health data in the cloud for easy access by guardians, family doctors, or medical institutions at any time. Through the long-term accumulated data, the system can track the changing trends of the elderly's health status and provide support for disease prevention and health management.

[0047] Example 2

[0048] Please refer to Figure 1 , which is the second embodiment of the present invention. This embodiment provides a method for analyzing the physical state of the elderly by detecting the air composition in the bedroom, including the following steps:

[0049] Device Installation and Setup: Install the air composition collection device (sensor array) in the indoor areas where the elderly often move, such as the bedroom, living room, etc. During installation, ensure that the position of the sensor array is not blocked and can collect the VOC components in the air in real time. Connect the device to the home Wi-Fi network so that the data can be uploaded to the central processing unit for analysis in real time.

[0050] Device Startup and Initialization: After the user starts the device, the system will automatically perform initialization settings, including sensor calibration, environmental parameter collection (temperature, humidity, etc.), and network connection configuration. Once the device successfully connects to the network, the sensor will start collecting air composition data in real time and transmit the data to the central processing unit through the wireless communication module.

[0051] Data Collection and Health Assessment: The device will automatically collect the VOC concentration data in the air during operation and analyze the data in real time. The system will generate health reports regularly to evaluate the physical condition of the elderly. The system provides real-time health assessment by analyzing the correlation between gas concentration and the health status of the elderly. For example, when the acetone concentration increases, the system will remind the user to pay attention to diabetes-related symptoms.

[0052] Environmental Regulation and Interference Elimination: The system will monitor the indoor environmental conditions in real time and automatically adjust the air quality through the environmental regulation module. For example, when the humidity is too high or the air circulation is poor, the system will automatically activate the air conditioner, humidifier, or fan to ensure that the sensor can accurately collect the VOC components in the air. The system combines the environmental data with the collected VOC data for calibration and data compensation to ensure that the monitoring results are not affected by environmental changes.

[0053] Feedback and Alarm: When the system detects an abnormal health status of the elderly, it will immediately issue an alarm to notify the guardian or medical staff. Through the mobile application, the guardian can view the real-time health assessment results of the elderly and take corresponding intervention measures in a timely manner. If the health problem is relatively serious, the system will automatically send the health data to the medical institution or emergency contact.

[0054] Data storage and analysis: All collected health data will be automatically uploaded to the cloud for storage and can be viewed at any time by authorized personnel (such as family doctors, healthcare providers, etc.); by analyzing long-term health data, the system can identify trends in health changes and provide customized health management advice to users.

[0055] The environmental regulation module of the present invention can intelligently adjust the indoor temperature, humidity, and air circulation to ensure that the sensor can stably and accurately collect the VOC components in the air; changes in environmental factors (such as temperature and humidity) often interfere with the concentration measurement of VOCs, and it is difficult for traditional systems to effectively remove this interference; while the present invention controls devices such as air conditioners, humidifiers, and fans to maintain the stability of indoor air quality, thereby eliminating environmental interference and improving the accuracy of data collection.

[0056] Traditional technologies often use a single type of sensor, and this method has limited early warning capabilities for some complex diseases or health conditions; by combining multiple highly selective sensors (such as metal oxide semiconductor sensors, optical sensors, electrochemical sensors, etc.), the present invention can monitor multiple VOC components with high precision, and optimize the selectivity and sensitivity of the sensors for different diseases or health conditions to improve the overall accuracy of health assessment; for example, by measuring the concentration changes of different chemical components such as formaldehyde, ethanol, and acetone, the system can determine whether there are health problems such as diabetes, cardiovascular diseases, or respiratory diseases.

[0057] Most of the health monitoring systems in the prior art adopt traditional threshold judgment methods, while the present invention uses machine learning algorithms to comprehensively judge the health status of the elderly based on the concentration data of multiple VOC components; the system establishes an association model between the concentration of VOC components and specific diseases (such as diabetes, respiratory diseases, etc.) by training a large amount of health data; when the system detects that the VOC concentration exceeds the normal range, it will use the algorithm to evaluate the physical condition of the elderly in real time and determine whether there are potential health problems; this intelligent evaluation can greatly improve the accuracy and early warning capabilities of health monitoring.

[0058] Traditional health monitoring systems usually only provide local data display or recording and lack real-time interaction with guardians and doctors; the present invention transmits the health assessment results and alarm information to guardians or medical personnel in real time through a wireless communication module; through a mobile application or web page, guardians can view the health data of the elderly and timely understand the changes in their health status; if the health problem is relatively serious, the system will automatically send an alarm to the doctor or emergency contact to ensure timely intervention; this intelligent alarm function greatly improves the response speed of health management and avoids serious consequences caused by the failure to handle health abnormalities in a timely manner.

[0059] Compared with traditional health monitoring devices, the present invention introduces cloud storage and analysis functions, enabling all monitoring data to be stored long-term and trend analysis to be performed; not only facilitating access to health data by guardians and doctors at any time, but also providing personalized guidance for the health management of the elderly through the long-term accumulated data; for example, the system can provide the change trend of the health status of the elderly to doctors or guardians based on the results of long-term health data analysis, helping to predict potential health risks; in addition, the cloud storage of data also facilitates large-scale accumulation and sharing of health data, providing a basis for future health big data research;

[0060] Traditional health monitoring methods usually require direct contact with or invasion of the elderly's body (such as blood glucose monitoring, blood pressure measurement, etc.), and these methods are not only uncomfortable but also likely to make the elderly feel discomfort; in contrast, the present invention realizes health monitoring by analyzing the VOC components in the air, which is completely non-invasive and can operate all day long, and the elderly do not need to change their daily living habits; the sensors are arranged in the areas where the elderly often move at home to monitor the indoor air composition in real time without disturbing the normal life of the elderly;

[0061] Existing health monitoring technologies often evaluate based on standardized health data thresholds, lacking consideration of individual differences; the present invention analyzes the health data of the elderly individuals through intelligent algorithms to provide personalized health assessments and recommendations; for example, the system can give more accurate health guidance based on factors such as the daily activities of the elderly, historical health data, genetic information, etc., to help formulate personalized health care measures or intervention suggestions.

[0062] Although the embodiments of the present invention have been shown and described, see the above detailed description, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom, characterized in that: The steps include: Install sensor arrays in indoor environments where the elderly often live or move around to detect VOC components in the air in real time; The sensors collect data every 1-5 minutes and transmit the data to the central processing unit for processing; After receiving the sensor data, the central processing unit performs data correction and denoises the sensor output signal to eliminate interference caused by environmental changes; The corrected data is used through a built-in algorithm model to evaluate the changing trend of the current indoor air composition and determine the physical condition of the elderly; Based on the trained machine learning model, the system analyzes the correlation between VOC concentration in the air and the health status of the elderly to determine whether there are health abnormalities; If health abnormalities are detected, the system sends an alarm message to the guardian or medical staff through the communication module; Guardians view the elderly’s health reports through mobile devices and intervene based on prompts; The system automatically adjusts indoor air quality based on environmental conditions; The sensor continuously performs self-correction through a feedback mechanism to ensure the reliability of the monitoring data.

2. The method for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom according to claim 1, characterized in that: The central processing unit includes a microprocessor, a data storage unit and a communication module, and processes, stores and transmits data in real time.

3. The method for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom according to claim 1, characterized in that: The communication module transmits the health assessment results and warning information to mobile phones and tablet computer terminal devices.

4. The method for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom according to claim 1, characterized in that: It also includes environmental conditioning, which includes controlling ventilation, humidity and temperature in the room.

5. The method for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom according to claim 1, characterized in that: The machine learning model is trained using a large amount of clinical data.

6. The method for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom according to claim 1, characterized in that: Interference caused by environmental changes includes changes in temperature and humidity.

7. A device for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom, characterized in that: include The air composition collection device uses a highly sensitive sensor array to detect VOC components in indoor air; The data acquisition and processing module converts the detected VOC concentration data into digital signals and transmits them to the central processing unit for further processing; Air quality adjustment and environmental interference elimination module, which controls indoor ventilation, humidity and temperature, and reduces the interference of the environment on the sensor detection results; The data analysis and health assessment algorithm module uses a machine learning-based algorithm to analyze the collected air composition data to achieve real-time assessment of the physical condition of the elderly; The real-time monitoring and feedback system sends timely alerts to guardians or medical staff when the health status of the elderly changes.

8. The device for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom according to claim 7, characterized in that: The air quality regulation and environmental interference elimination module is regulated through intelligent fans, humidifiers and air conditioning systems.

9. The device for analyzing the physical condition of an elderly person by detecting the air composition in a bedroom according to claim 7, characterized in that: The real-time monitoring and feedback system transmits health assessment results and warning information to mobile phones and tablet computer terminal devices through wireless communication modules.

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