Elderly user activity monitoring system

Abstract

According to the technical scheme, the elderly user activity monitoring system is characterized in that the elderly user activity monitoring system comprises wearable medical equipment, the wearable medical equipment is in communication connection with terminal equipment, and the wearable medical equipment comprises a data acquisition module, a data preprocessing module and a data analysis module; the data acquisition module is used for acquiring acceleration signals generated by human body activities, pulse data of a human body and oxyhemoglobin saturation data, the data preprocessing module is used for preprocessing the acceleration signals, high-pass filtering is carried out on the acceleration signals through a high-pass filter to obtain acceleration data, normalization processing is carried out on the acceleration data, and the normalized acceleration data are sent to the data processing module; performing low-pass filtering on the acceleration data through a low-pass filter; the system has the technical effects that medical aid can be adopted in time, the possibility of aggravation of the illness state of the old people is reduced, the monitoring pressure of guardians on the old people is relieved, and the safety of daily activities of the old people is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring systems, and in particular to an activity monitoring system for elderly users. Background Art

[0002] As people's living standards improve, health becomes a new lifestyle that people pursue. As an important physiological parameter of the human body, blood oxygen saturation has been widely used in clinical practice. An oximeter is an instrument that detects blood oxygen saturation and pulse rate in human blood. The oximeter uses the part to be tested (such as a finger) as a transparent container for hemoglobin. When measuring blood oxygen, the difference between the absorption of red light (660nm) and infrared light (910nm) by reduced hemoglobin and oxygenated hemoglobin is detected to determine the blood oxygen saturation.

[0003] Chinese patent publication number CN105223801A discloses a watch suitable for health monitoring and satellite positioning of the elderly. The appearance of the watch is similar to that of an ordinary watch. It is provided with a dial and can be used to view time. In the dial of the watch, an ultra-micro and ultra-thin somatosensory detection system is provided, including: a detector, a data analyzer, and an alarm. There is also an ultra-thin GPS positioning system and a transmitter. The normal range of various physical health indicators of the elderly is pre-set in the health monitoring and satellite positioning watch for the elderly. Through the built-in somatosensory detection system, the changes in the heart rate, body temperature, and blood pressure of the elderly are fully monitored. Once an indicator exceeds the normal range, the problem is immediately displayed and an alarm is issued. The data on the health status is transmitted to the hospital and the elderly's children, and the hospital arrives in time through GPS positioning. The present invention can accurately and quickly monitor the health status of the elderly in real time, ensuring the health of the elderly.

[0004] The monitoring system of the above patent is used to monitor the heart rate, body temperature and blood pressure data of the elderly. When the data exceeds the threshold, it is sent to the children. However, the system does not monitor the acceleration signal generated by the movement of the elderly, the pulse data of the human body and the blood oxygen saturation data. It cannot obtain the situation of the elderly falling, and cannot realize the networking of the monitoring system. Medical staff will not be able to understand the patient's physiological condition in time and cannot quickly take necessary medical intervention, which puts the patient in a more dangerous state and makes the elderly patients unable to receive timely treatment. Summary of the invention

[0005] The purpose of the present invention is to provide an activity monitoring system for elderly users, which has the advantages of being able to take medical aid in time, reducing the possibility of the elderly's condition getting worse, alleviating the pressure on guardians to monitor the elderly, and improving the safety of the elderly's daily activities.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: an elderly user activity monitoring system, comprising a wearable medical device, the wearable medical device is communicatively connected to a terminal device, the wearable medical device comprises a data acquisition module, a data preprocessing module and a data analysis module; The data acquisition module is used to collect acceleration signals generated by human activities, human pulse data and blood oxygen saturation data; The data preprocessing module is used to preprocess the acceleration signal, obtain acceleration data after high-pass filtering the acceleration signal through a high-pass filter, normalize the acceleration data, and low-pass filter the acceleration data through a low-pass filter; The data analysis module uses a peak-valley detection algorithm to realize the statistics of user activity, adopts a SVM algorithm to realize the fall monitoring of the elderly and can send an alarm SMS via GPRS when a fall occurs, sets the alarm thresholds of pulse and blood oxygen saturation, and can send an alarm SMS via GPRS when the system detects that the data exceeds the threshold range; The terminal device is used to receive, display and store human activity data, communicate with the wearable medical device through the Bluetooth communication module to transmit data, display the amount of exercise and real-time pulse and blood oxygen data of the guardian, and is used to understand the physical condition of the guardian.

[0007] The present invention is further configured as follows: the data acquisition module includes an acceleration acquisition module, a pulse acquisition module and a blood oxygen acquisition module, the acceleration acquisition module acquires acceleration signals generated by human activities through a three-axis acceleration sensor, the pulse acquisition module acquires human pulse data through a pulse sensor, the blood oxygen acquisition module acquires human blood oxygen saturation data through a blood oxygen sensor, and the blood oxygen acquisition module is communicatively connected to a physiological parameter module.

[0008] The present invention is further configured as follows: the physiological parameter detection module includes a data communication module, a waveform display module and a physiological parameter calculation module, the data communication module is used to transmit the data collected by the blood oxygen collection module to the terminal device for communication, the waveform display module uses a timer to read the transmitted data every 0.1-0.2 seconds, extracts the PPG signal data and draws it to a graphic control, and the physiological parameter calculation module processes and calculates the collected data to obtain the heart rate.

[0009] The present invention is further configured as follows: the calculation method of the physiological parameter calculation module specifically uses the MDR algorithm to detect and eliminate motion artifacts on the signal, extract high-quality signal segments, and then use the heart rate calculation formula to calculate the corresponding heart rate.

[0010] The present invention is further configured as follows: the terminal device includes a storage module, an alarm module and a medical recommendation module, the storage module is used to receive data transmitted by the data acquisition module, the alarm module is used to receive an alarm signal sent by the data analysis module, and the medical recommendation module recommends a corresponding medical rescue plan according to a personalized recommendation algorithm.

[0011] The present invention is further configured as follows: the medical rescue plan specifically obtains feature data of the guardian through a feature acquisition module, and sends the feature data to a matching module, and the matching module is used to match the feature data with treated user data in a database and recommend corresponding hospital information.

[0012] The present invention is further configured as follows: the feature acquisition module is used to obtain symptom keyword information input by the guardian, perform Chinese word segmentation on the keyword information through the TF-IDF function, obtain the word segmentation result, and send the word segmentation result to the matching module.

[0013] The present invention is further configured as follows: the matching module is used to obtain analysis results, send the word segmentation results to big data for retrieval, and match the treatment plans in the big data according to the priority of the retrieval results.

[0014] The present invention is further configured as follows: the alarm module includes a voice module, a display module and a control module, the voice module is used for voice calls with the wearable medical device, the control module is used to control the speaker on the wearable medical device to issue a voice alarm, and the display module is used to send the symptoms and precautions of the guardian to the display on the wearable device.

[0015] The present invention is further configured as follows: the hospital information includes geographical information, contact information, establishment time and visiting doctor information.

[0016] To summarize, this system aims at the current situation where most middle-aged elderly people are unattended. The elderly wear wearable medical devices, which collect acceleration signals, human pulse data and blood oxygen saturation data generated by human activities. The peak and valley detection algorithm and the fall detection algorithm based on SMO-VM are used to realize the activity monitoring and fall detection of the elderly. The threshold range of pulse and blood oxygen saturation is set. When the collected acceleration signal, human pulse data and blood oxygen saturation data exceed the threshold, an alarm signal is sent to the terminal device. After receiving the alarm signal, the terminal device can take medical rescue in time to reduce the possibility of worsening of the elderly's condition, reduce the pressure of guardians on the elderly, and improve the safety of the elderly's daily activities. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is the overall framework diagram of the system of this embodiment; Figure 2This embodiment is used to embody the framework diagram of the wearable medical device; Figure 3 This is a framework diagram of a physiological parameter detection module used in this embodiment; Figure 4 This is a framework diagram of a data acquisition module used in this embodiment; Figure 5 This embodiment is used to reflect the terminal device framework diagram; Figure 6 This is a framework diagram of an alarm module used in this embodiment. DETAILED DESCRIPTION

[0018] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0019] Example 1: Referring to Figure 1-6As shown, an activity monitoring system for elderly users includes a wearable medical device, which is communicatively connected to a terminal device. The wearable medical device includes a data acquisition module, a data preprocessing module and a data analysis module. The data acquisition module is used to collect acceleration signals, pulse data and blood oxygen saturation data generated by human activities. The data preprocessing module is used to preprocess the acceleration signals, obtain acceleration data after high-pass filtering the acceleration signals through a high-pass filter, normalize the acceleration data, and low-pass filter the acceleration data through a low-pass filter. The data analysis module implements statistics of user activity through a peak and valley detection algorithm, adopts an SVM algorithm to implement fall monitoring for the elderly and can send alarm text messages through GPRS when a fall occurs, sets alarm thresholds for pulse and blood oxygen saturation, and can send alarm text messages through GPRS when the system detects that the data exceeds the threshold range. The terminal device is used to receive, display and store human activity data, and transmits data through a Bluetooth communication module to communicate with the wearable medical device, and displays the amount of exercise and real-time pulse and blood oxygen data of the guardian, which is used to understand The physical condition of the person under guardianship, the data acquisition module includes an acceleration acquisition module, a pulse acquisition module and a blood oxygen acquisition module. The acceleration acquisition module acquires the acceleration signal generated by human activities through a three-axis acceleration sensor, the pulse acquisition module acquires the pulse data of the human body through a pulse sensor, and the blood oxygen acquisition module acquires the blood oxygen saturation data of the human body through a blood oxygen sensor. The blood oxygen acquisition module is connected to the physiological parameter module for communication. This system aims at the current situation where most middle-aged elderly people are unattended. The elderly wear wearable medical devices. The wearable medical devices acquire the acceleration signal generated by human activities, the pulse data of the human body and the blood oxygen saturation data. The peak and valley detection algorithm and the fall detection algorithm based on SMO-VM are adopted to realize the activity monitoring and fall detection of the elderly. The threshold range of pulse and blood oxygen saturation is set. When the acquired acceleration signal, the pulse data of the human body and the blood oxygen saturation data exceed the threshold, an alarm signal is sent to the terminal device. After obtaining the alarm signal, the terminal device can take medical rescue in time to reduce the possibility of worsening of the elderly's condition, reduce the guardian's supervision pressure on the elderly, and improve the safety of the elderly's daily activities.

[0020] Embodiment 2: The physiological parameter detection module includes a data communication module, a waveform display module and a physiological parameter calculation module. The data communication module is used to transmit the data collected by the blood oxygen collection module to the terminal device for communication. The waveform display module uses a timer to read the transmitted data every 0.1-0.2 seconds, extracts the PPG signal data and draws it to the graphic control. The physiological parameter calculation module processes and calculates the collected data to obtain the heart rate. The calculation method of the physiological parameter calculation module is specifically to use the MDR algorithm to detect and eliminate motion artifacts on the signal, extract high-quality signal segments, and then use the heart rate calculation formula to calculate the corresponding heart rate.

[0021] Embodiment 3: The terminal device includes a storage module, an alarm module and a medical recommendation module. The storage module is used to receive data transmitted by the data acquisition module. The alarm module is used to receive alarm signals sent by the data analysis module. The medical recommendation module recommends corresponding medical rescue plans based on a personalized recommendation algorithm. The medical rescue plan specifically obtains feature data of the guardian through a feature acquisition module, and sends the feature data to a matching module. The matching module is used to match the feature data with the treated user data in the database and recommend corresponding hospital information.

[0022] Embodiment 4: The feature acquisition module is used to obtain the symptom keyword information input by the guardian, perform Chinese word segmentation on the keyword information through the TF-IDF function, obtain the word segmentation result, and send the word segmentation result to the matching module. The matching module is used to obtain the analysis result, send the word segmentation result to the big data for retrieval, and match the treatment plan in the big data according to the priority of the retrieval result.

[0023] Embodiment 5: The alarm module includes a voice module, a display module and a control module. The voice module is used for voice calls with the wearable medical device. The control module is used to control the speaker on the wearable medical device to issue a voice alarm. The display module is used to send the symptoms and precautions of the guardian to the display on the wearable device. The hospital information includes geographic information, contact information, establishment time and doctor information.

[0024] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. An elderly user activity monitoring system, characterized in that: The wearable medical device includes a wearable medical device, the wearable medical device is communicatively connected to a terminal device, and the wearable medical device includes a data acquisition module, a data preprocessing module, and a data analysis module; The data acquisition module is used to collect acceleration signals generated by human activities, human pulse data and blood oxygen saturation data; The data preprocessing module is used to preprocess the acceleration signal, obtain acceleration data after high-pass filtering the acceleration signal through a high-pass filter, normalize the acceleration data, and low-pass filter the acceleration data through a low-pass filter; The data analysis module uses a peak-valley detection algorithm to realize the statistics of user activity, adopts a SVM algorithm to realize the fall monitoring of the elderly and can send an alarm SMS via GPRS when a fall occurs, sets the alarm thresholds of pulse and blood oxygen saturation, and can send an alarm SMS via GPRS when the system detects that the data exceeds the threshold range; The terminal device is used to receive, display and store human activity data, communicate with the wearable medical device through the Bluetooth communication module to transmit data, display the amount of exercise and real-time pulse and blood oxygen data of the guardian, and is used to understand the physical condition of the guardian.

2. The elderly user activity monitoring system according to claim 1, characterized in that: The data acquisition module includes an acceleration acquisition module, a pulse acquisition module and a blood oxygen acquisition module. The acceleration acquisition module acquires acceleration signals generated by human activities through a three-axis acceleration sensor, the pulse acquisition module acquires human pulse data through a pulse sensor, and the blood oxygen acquisition module acquires human blood oxygen saturation data through a blood oxygen sensor. The blood oxygen acquisition module is communicatively connected to a physiological parameter module.

3. The elderly user activity monitoring system according to claim 2, characterized in that: The physiological parameter detection module includes a data communication module, a waveform display module and a physiological parameter calculation module. The data communication module is used to transmit the data collected by the blood oxygen collection module to the terminal device for communication. The waveform display module uses a timer to read the transmitted data every 0.1-0.2 seconds, extracts the PPG signal data and draws it to the graphic control. The physiological parameter calculation module processes and calculates the collected data to obtain the heart rate.

4. The elderly user activity monitoring system according to claim 2, characterized in that: The calculation method of the physiological parameter calculation module is specifically to use the MDR algorithm to detect and eliminate motion artifacts on the signal, extract high-quality signal segments, and then use the heart rate calculation formula to calculate the corresponding heart rate.

5. The elderly user activity monitoring system according to claim 1, characterized in that: The terminal device includes a storage module, an alarm module and a medical recommendation module. The storage module is used to receive data transmitted by the data acquisition module, the alarm module is used to receive alarm signals sent by the data analysis module, and the medical recommendation module recommends corresponding medical rescue plans based on a personalized recommendation algorithm.

6. The elderly user activity monitoring system according to claim 5, characterized in that: The medical rescue plan specifically obtains the characteristic data of the guardian through the characteristic acquisition module, and sends the characteristic data to the matching module. The matching module is used to match the characteristic data with the treated user data in the database and recommend corresponding hospital information.

7. The elderly user activity monitoring system according to claim 6, characterized in that: The feature acquisition module is used to obtain the symptom keyword information input by the guardian, perform Chinese word segmentation on the keyword information through the TF-IDF function, obtain the word segmentation result, and send the word segmentation result to the matching module.

8. The elderly user activity monitoring system according to claim 6, characterized in that: The matching module is used to obtain analysis results, send the segmentation results to big data for retrieval, and match the treatment plans in the big data according to the priority of the retrieval results.

9. The elderly user activity monitoring system according to claim 5, characterized in that: The alarm module includes a voice module, a display module and a control module. The voice module is used for voice calls with the wearable medical device, the control module is used to control the speaker on the wearable medical device to issue a voice alarm, and the display module is used to send the symptoms and precautions of the guardian to the display on the wearable device.

10. The elderly user activity monitoring system according to claim 6, characterized in that: The hospital information includes geographical information, contact information, establishment time and visiting doctor information.

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