Early warning method and device for abnormal activity of home-based care personnel

Abstract

The invention discloses an early warning method and device for activity abnormity of home-based care personnel, and relates to the technical field of home-based care, according to the early warning method and device for activity abnormity of home-based care personnel, body data of old people is collected through a smart bracelet, visitor information data is obtained through a prompt doorbell, and multi-dimensional data collection is achieved; data transmission is carried out by adopting technologies such as 5G and Bluetooth, and the data is encrypted, so that safe and reliable transmission of the data is ensured, and a rich and accurate data basis is provided for subsequent analysis; the cloud analysis platform analyzes the data of the elderly and judges the abnormal state based on a preset threshold value in combination with various characteristics, the abnormal condition of the elderly can be timely and accurately found, and the early warning accuracy is improved; a grading early warning mechanism is set, first-level early warning is generated when abnormity occurs, relatives and a community service center are informed through multiple modes such as mobile voice and data communication, meanwhile, doorbell flashing is prompted, nearby help calling is achieved, and rescue timeliness is improved; and when no response exists in the preset time, third-level early warning is upgraded.

Description

Technical Field

[0001] The present invention relates to the technical field of home-based elderly care, and in particular to a method and device for early warning of abnormal activities of home-based elderly care personnel. Background Art

[0002] The existing methods and devices for warning of abnormal activities of elderly people living at home still have the following drawbacks in actual use:

[0003] Generally, video surveillance is used to install cameras in key areas where the elderly live, such as living rooms, bedrooms, and bathrooms, and use video analysis technology to monitor the elderly's activities in real time. The elderly's behavior and posture can be identified to determine whether there are any abnormalities such as falls or long periods of inactivity. Alternatively, a variety of sensors are used to collect information on the elderly's activities. For example, sensors are installed in doors, windows, floors, furniture, and other locations in the elderly's room to detect the elderly's movement, touch, and other actions to determine their activity status.

[0004] Some elderly people are not familiar with new technologies and may feel fear or distrust of these early warning devices and be unwilling to cooperate in their use; some elderly people may feel that being monitored by these devices is an interference in their lives, affecting their freedom and independence, and thus refuse to use them. In addition, the installation and use of these early warning devices require certain expenses, including equipment purchase, installation and debugging, network communication, and subsequent maintenance and upgrade costs, which may be unaffordable for some families with poor economic conditions.

[0005] However, if only a smart bracelet is worn, the function is too single. When encountering an emergency, the service personnel cannot understand and rescue the elderly in time; this makes the device have certain shortcomings when used. Summary of the Invention

[0006] The purpose of the present invention is to provide a method and device for early warning of abnormal activities of elderly people living at home, so as to solve the above-mentioned problems.

[0007] In order to achieve the above-mentioned object, the present invention provides the following technical solution: a method and device for early warning of abnormal activities of elderly people living at home, comprising the following steps:

[0008] S1. Data Collection: Use smart bracelets to obtain real-time heart rate, blood oxygen, and motion acceleration data of the elderly; obtain visitor information data through doorbell prompts;

[0009] S2. Data transmission: The doorbell uses the 5G communication module to upload the integrated data via Bluetooth to the smart bracelet and cloud analysis platform. The data from the smart bracelet is also uploaded to the cloud analysis platform.

[0010] S3. Abnormality determination: The cloud analysis platform analyzes heart rate, blood oxygen and motion acceleration data based on preset thresholds, and combines the characteristics of sudden changes in respiratory rate or sudden stops in limb trajectory to determine whether the elderly person is in an abnormal state.

[0011] Furthermore, the data collection specifically includes:

[0012] The high-precision sensors in smart bracelets accurately monitor various body data of the elderly. However, when the elderly do not carry the smart bracelet for various reasons, its monitoring function will be in trouble. Since the bracelet is separated from the elderly, it can no longer obtain key body data such as heart rate and exercise status in real time. Data transmission is interrupted, triggering the corresponding reminder mechanism;

[0013] The doorbell is equipped with a high-definition camera and a wide-angle lens, which can record the situation in front of the door within the monitoring range in all directions and without blind spots. Whether someone rings the doorbell or there is abnormal movement in front of the door, the doorbell will immediately start the recording function, store the scene in the form of high-definition video in the local cache and upload it.

[0014] Furthermore, the data collection further includes:

[0015] The smart bracelet has a built-in high-sensitivity microphone and speaker. The smart bracelet can communicate with people outside the door through the reminder doorbell. When a visitor rings the reminder doorbell, the reminder doorbell will send a notification to the smart bracelet worn by the elderly through the interactive system. After receiving the notification, the smart bracelet will remind the elderly by vibration and ringtone. The elderly can talk to the people outside the door directly through the smart bracelet. It can clearly capture the elderly’s voice and transmit it to the reminder doorbell end, and at the same time play the voice of the people outside the door clearly to the elderly.

[0016] Furthermore, the data transmission specifically includes:

[0017] The doorbell uses a built-in 5G communication module to transmit the integrated image, sound, and behavior analysis data in an encrypted form to the smart bracelet using Bluetooth Low Energy (BLE) technology. BLE technology, with its low power consumption and high stability in short-range communication, reliably transmits data between the doorbell and the bracelet.

[0018] The cloud-based analysis platform further cleans, categorizes, and stores various data received from smart bracelets and doorbells. For image data, a convolutional neural network (CNN) is used to identify the visitor's facial features and compare them with the visitor database in the interactive system. If the visitor is identified as a pre-registered friend or relative, the visitor's identity information is marked in the system. For sound data, a more in-depth semantic analysis is performed to extract key voice information.

[0019] Furthermore, the abnormality determination specifically includes:

[0020] Level-by-level warning: If it is determined to be abnormal, the cloud platform will generate a level-one warning instruction;

[0021] Communication linkage: Automatically call the elderly person's bound relative number through mobile voice service, send mobile data communication messages containing location information to the community service center, and send flashing light prompts to the doorbell to call for help nearby;

[0022] No response upgrade: If no response is received from relatives or the elderly within the preset time, it will be upgraded to a third-level warning and the service personnel will be authorized to unlock the door with the NFC key.

[0023] Furthermore, the method of automatically calling the elderly person's bound relative number through a mobile voice service, simultaneously sending a mobile data communication message containing location information to a community service center, and sending a flashing light prompt to a doorbell to call for help nearby, further includes:

[0024] Inform the family members of any abnormal situation through the relatives’ phone number so that they can understand the elderly’s situation in a timely manner;

[0025] By sending communication messages to the service center in the equipment area, service personnel can arrive at the elderly's residence in time to understand the situation and make further arrangements;

[0026] By sending a flashing light prompt through the reminder doorbell, passers-by can be alerted and asked for help; pedestrians can quickly press the emergency button clearly marked on the reminder doorbell. After the elderly see the request prompt on the smart bracelet, if they confirm to allow it, the built-in sensor of the reminder doorbell will immediately capture this button action, triggering the corresponding data collection and transmission process to open the door.

[0027] Furthermore, the no-response upgrade further includes:

[0028] Identity verification: The service staff touches the doorbell with the NFC key, triggering the camera to capture the face image;

[0029] Blockchain evidence storage: The facial image is compared with the service personnel's pre-recorded information, and the verification results are written into the blockchain node via fiber optic broadband;

[0030] Unlock record: After successful verification, an unlock record is generated, which includes a timestamp, personnel ID, and real-time video footage transmitted by the 5G network slice.

[0031] A device for early warning of abnormal activities of elderly people living at home, comprising:

[0032] Smart bracelet module: acquires the elderly's heart rate, blood oxygen and motion acceleration data, and transmits them to the cloud analysis platform via Bluetooth;

[0033] Doorbell module: acquires information data of service personnel and uploads the integrated data to the smart bracelet and cloud analysis platform via Bluetooth;

[0034] NFC identity verification module: Linked with the doorbell camera, it verifies the service personnel's biometrics and connects to the blockchain evidence storage platform via fiber optic broadband;

[0035] Cloud analysis module: acquires data information from the smart bracelet module and the doorbell module, and further cleans, classifies and stores it for executing any of the method steps described in claims 1-7.

[0036] Compared with the prior art, the method and device for early warning of abnormal activities of elderly people at home provided by the present invention have the following beneficial effects:

[0037] The method and device for warning abnormal activities of elderly people at home collect the physical data of the elderly through smart bracelets, prompt the doorbell to obtain visitor information data, and realize multi-dimensional data collection; and adopt 5G, Bluetooth and other technologies for data transmission, and encrypt the data to ensure the safe and reliable transmission of data, providing a rich and accurate data basis for subsequent analysis; the cloud analysis platform analyzes the elderly data based on preset thresholds and combines multiple features to determine abnormal conditions, which can timely and accurately detect abnormal conditions of the elderly and improve the accuracy of warnings; set up a hierarchical warning mechanism, generate a first-level warning when an abnormality occurs, and notify relatives and community service centers through mobile voice, data communication and other methods. The reminder doorbell will flash in time, so that the nearest help can be called and the rescue will be timely improved; if there is no response within the preset time, it will be upgraded to the third level warning, and the service personnel will be authorized to unlock the door with the NFC key. Strict identity verification will be carried out before unlocking and blockchain evidence will be stored, which not only protects the safety of the elderly but also ensures the traceability of the operation; the smart bracelet and the reminder doorbell can realize two-way communication, which is convenient for the elderly to communicate with people outside the door and increase their sense of security and convenience; the smart bracelet, reminder doorbell, NFC identity verification, cloud analysis and other modules work together to form a complete warning system, covering data collection, transmission, analysis, warning and emergency response, etc., effectively improving the safety and service quality of home-based elderly care. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0039] Figure 1 It is a schematic diagram of the overall structure of the method of the present invention;

[0040] Figure 2 Schematic diagram of the method structure of the present invention. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0042] See also Figure 1 、 2 A method and device for early warning of abnormal activities of elderly people living at home, comprising the following steps:

[0043] S1. Data Collection: Use smart bracelets to obtain real-time heart rate, blood oxygen, and motion acceleration data of the elderly; obtain visitor information data through doorbell prompts;

[0044] S2. Data transmission: The doorbell uses the 5G communication module to upload the integrated data via Bluetooth to the smart bracelet and cloud analysis platform. The data from the smart bracelet is also uploaded to the cloud analysis platform.

[0045] S3. Abnormality determination: The cloud analysis platform analyzes heart rate, blood oxygen and motion acceleration data based on preset thresholds, and combines the characteristics of sudden changes in respiratory rate or sudden stops in limb trajectory to determine whether the elderly person is in an abnormal state.

[0046] Data collection, including:

[0047] The high-precision sensors in smart bracelets accurately monitor various body data of the elderly. However, when the elderly do not carry the smart bracelet for various reasons, its monitoring function will be in trouble. Since the bracelet is separated from the elderly, it can no longer obtain key body data such as heart rate and exercise status in real time. Data transmission is interrupted, triggering the corresponding reminder mechanism;

[0048] The heart rate sensor in the smart bracelet uses photoelectric sensing technology to monitor heart rate in real time by detecting changes in blood's absorption of light; the blood oxygen sensor uses the principle of spectrophotometry to measure the absorption of light of a specific wavelength when passing through human tissue, thereby calculating the blood oxygen content; the motion acceleration sensor is based on MEMS (micro-electromechanical system) technology, which can sense the acceleration changes of the elderly in all directions, and then calculate information such as the number of steps and exercise speed.

[0049] Heart rate calculation: by detecting the time interval T between two adjacent heartbeat signals i , calculate the average heartbeat interval time, heart rate HR calculation formula is in n is the number of collected heartbeat intervals; the smart bracelet collects heart rate data at a frequency of multiple times per second, and performs preliminary processing and integration through the built-in microprocessor, and then transmits the data to the cloud analysis platform through the Bluetooth module.

[0050] Calculation of exercise steps: The acceleration data a(t) collected by the motion acceleration sensor will fluctuate with the movement of the elderly; by setting an acceleration threshold a th , when |a(t)|>a th And when specific waveform characteristics are met, it is determined to be a step; the specific judgment can be made by analyzing the time domain characteristics of the acceleration data, such as peak values, valley values, etc.

[0051] The doorbell is equipped with a high-definition camera and a wide-angle lens. The high-definition camera uses a CMOS image sensor with high resolution and good low-light performance, which can clearly capture the scene in front of the door; the wide-angle lens has a viewing angle of up to 120°-180°, ensuring that there are no blind spots in the monitoring area in front of the door, and can record the situation in front of the door within the monitoring range in all directions and without blind spots. Whether someone visits and rings the doorbell, or there is any abnormal movement in front of the door, the doorbell will immediately start the recording function, store the live scene in the form of high-definition video in the local cache and upload it.

[0052] Data collection also includes:

[0053] The smart bracelet has a built-in high-sensitivity microphone and speaker. The smart bracelet can communicate with people outside the door through the reminder doorbell. When a visitor rings the reminder doorbell, the reminder doorbell will send a notification to the smart bracelet worn by the elderly through the interactive system. After receiving the notification, the smart bracelet will remind the elderly by vibration and ringtone. The elderly can talk to the people outside the door directly through the smart bracelet. It can clearly capture the elderly’s voice and transmit it to the reminder doorbell end, and at the same time play the voice of the people outside the door clearly to the elderly.

[0054] Data transmission, specifically including:

[0055] The doorbell uses a built-in 5G communication module to transmit the integrated image, sound, and behavior analysis data in an encrypted form (using the AES-256 encryption algorithm, and the encryption key is regularly updated by the interactive system) to the smart bracelet using Bluetooth Low Energy (BLE) technology. Based on the low power consumption and high stability of BLE technology in short-range communication, the data is reliably transmitted between the doorbell and the bracelet.

[0056] The cloud-based analysis platform further cleans, categorizes, and stores various data received from smart bracelets and doorbells. For image data, a convolutional neural network (CNN) is used to identify the visitor's facial features and compare them with the visitor database in the interactive system. If the visitor is identified as a pre-registered friend or relative, the visitor's identity information is marked in the system. For sound data, a more in-depth semantic analysis is performed to extract key voice information.

[0057] Abnormal determination, including:

[0058] Level-by-level warning: If it is determined to be abnormal, the cloud platform will generate a level-one warning instruction;

[0059] Communication linkage: Automatically call the elderly person's bound relative number through mobile voice service, send mobile data communication messages containing location information to the community service center, and send flashing light prompts to the doorbell to call for help nearby;

[0060] No response upgrade: If no response is received from relatives or the elderly within the preset time, it will be upgraded to a third-level warning and the service personnel will be authorized to unlock the door with the NFC key.

[0061] Abnormal state determination process: The cloud analysis platform pre-sets normal range thresholds for heart rate, blood oxygen and motion acceleration. These thresholds can be personalized based on factors such as the elderly's age and health status. For example, for generally healthy elderly people, the normal range of heart rate is set to 60-100 beats / minute, and the normal range of blood oxygen content is set to 95%-100%.

[0062] Respiratory frequency mutation judgment: Calculate the respiratory frequency f by collecting chest movement data from the smart bracelet or combining it with the respiratory sound characteristics from sound analysis breath , within a period of time t, record the number of breaths N breath ,but When the respiratory rate changes by more than a preset ratio (such as ±30%) in a short period of time (such as within 1 minute), It is determined to be a sudden change in respiratory rate; the judgment of sudden arrest of limb trajectory is based on motion acceleration data. When the motion acceleration continues to be lower than the minimum threshold (close to zero) within a certain period of time (such as 5 seconds), and other related sensor data (such as heart rate, blood oxygen, etc.) also show abnormal changes, it is determined to be a sudden arrest of limb trajectory; based on these data and characteristics, a logical judgment algorithm is used to determine whether the elderly person is in an abnormal state.

[0063] Automatically call the elderly person's registered relatives' phone number through mobile voice service, send mobile data communication messages containing location information to the community service center, and send flashing lights to the doorbell to call for help nearby. It also includes:

[0064] Inform the family members of any abnormal situation through the relatives’ phone number so that they can understand the elderly’s situation in a timely manner;

[0065] By sending communication messages to the service center in the equipment area, service personnel can arrive at the elderly's residence in time to understand the situation and make further arrangements;

[0066] By sending a flashing light prompt through the reminder doorbell, passers-by can be alerted and asked for help; pedestrians can quickly press the emergency button clearly marked on the reminder doorbell. After the elderly see the request prompt on the smart bracelet, if they confirm to allow it, the built-in sensor of the reminder doorbell will immediately capture this button action, triggering the corresponding data collection and transmission process to open the door.

[0067] Unresponsive upgrades also include:

[0068] Identity verification: The service staff touches the doorbell with the NFC key, triggering the camera to capture the face image;

[0069] Blockchain evidence storage: The facial image is compared with the service personnel's pre-recorded information, and the verification results are written into the blockchain node via fiber optic broadband;

[0070] Unlock record: After successful verification, an unlock record is generated, which includes a timestamp, personnel ID, and real-time video footage transmitted by the 5G network slice.

[0071] A device for early warning of abnormal activities of elderly people living at home, comprising:

[0072] Smart bracelet module: acquires the elderly's heart rate, blood oxygen and motion acceleration data, and transmits them to the cloud analysis platform via Bluetooth;

[0073] Doorbell module: acquires information data of service personnel and uploads the integrated data to the smart bracelet and cloud analysis platform via Bluetooth;

[0074] NFC identity verification module: Linked with the doorbell camera, it verifies the service personnel's biometrics and connects to the blockchain evidence storage platform via fiber optic broadband;

[0075] Cloud analysis module: acquires data information from the smart bracelet module and the doorbell module, and further cleans, classifies and stores it, for executing any method step of claims 1-7.

[0076] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

Claims

1. A method for early warning of abnormal activities of elderly people living at home, characterized in that: The following steps are involved: S1. Data Collection: Use smart bracelets to obtain real-time heart rate, blood oxygen, and motion acceleration data of the elderly; obtain visitor information data through doorbell prompts; S2. Data transmission: The doorbell uses the 5G communication module to upload the integrated data via Bluetooth to the smart bracelet and cloud analysis platform. The data from the smart bracelet is also uploaded to the cloud analysis platform. S3. Abnormality determination: The cloud analysis platform analyzes heart rate, blood oxygen and motion acceleration data based on preset thresholds, and combines the characteristics of sudden changes in respiratory rate or sudden stops in limb trajectory to determine whether the elderly person is in an abnormal state.

2. A method for early warning of abnormal activities of elderly people living at home according to claim 1, characterized in that: The data collection specifically includes: The high-precision sensors in smart bracelets accurately monitor various body data of the elderly. However, when the elderly do not carry the smart bracelet for various reasons, its monitoring function will be in trouble. Since the bracelet is separated from the elderly, it can no longer obtain key body data such as heart rate and exercise status in real time. Data transmission is interrupted, triggering the corresponding reminder mechanism; The doorbell is equipped with a high-definition camera and a wide-angle lens, which can record the situation in front of the door within the monitoring range in all directions and without blind spots. Whether someone rings the doorbell or there is abnormal movement in front of the door, the doorbell will immediately start the recording function, store the scene in the form of high-definition video in the local cache and upload it.

3. The method for early warning of abnormal activities of elderly people living at home according to claim 2, characterized in that: The data collection further includes: The smart bracelet has a built-in high-sensitivity microphone and speaker. The smart bracelet can communicate with people outside the door through the reminder doorbell. When a visitor rings the reminder doorbell, the reminder doorbell will send a notification to the smart bracelet worn by the elderly through the interactive system. After receiving the notification, the smart bracelet will remind the elderly by vibration and ringtone. The elderly can talk to the people outside the door directly through the smart bracelet. It can clearly capture the elderly’s voice and transmit it to the reminder doorbell end, and at the same time play the voice of the people outside the door clearly to the elderly.

4. The method for early warning of abnormal activities of elderly people living at home according to claim 1, characterized in that: The data transmission specifically includes: The doorbell uses a built-in 5G communication module to transmit the integrated image, sound, and behavior analysis data in an encrypted form to the smart bracelet using Bluetooth Low Energy (BLE) technology. BLE technology, with its low power consumption and high stability in short-range communication, reliably transmits data between the doorbell and the bracelet. The cloud-based analysis platform further cleans, categorizes, and stores various data received from smart bracelets and doorbells. For image data, a convolutional neural network (CNN) is used to identify the visitor's facial features and compare them with the visitor database in the interactive system. If the visitor is identified as a pre-registered friend or relative, the visitor's identity information is marked in the system. For sound data, a more in-depth semantic analysis is performed to extract key voice information.

5. The method for early warning of abnormal activities of elderly people living at home according to claim 1, characterized in that: The abnormality determination specifically includes: Level-by-level warning: If it is determined to be abnormal, the cloud platform will generate a level-one warning instruction; Communication linkage: Automatically call the elderly person's bound relative number through mobile voice service, send mobile data communication messages containing location information to the community service center, and send flashing light prompts to the doorbell to call for help nearby; No response upgrade: If no response is received from relatives or the elderly within the preset time, it will be upgraded to a third-level warning and the service personnel will be authorized to unlock the door with the NFC key.

6. The method for early warning of abnormal activities of elderly people living at home according to claim 5, characterized in that: The method of automatically calling the elderly person's bound relative number through a mobile voice service, simultaneously sending a mobile data communication message containing location information to a community service center, and sending a flashing light prompt to a doorbell to call for help nearby also includes: Inform the family members of any abnormal situation through the relatives’ phone number so that they can understand the elderly’s situation in a timely manner; By sending communication messages to the service center in the equipment area, service personnel can arrive at the elderly's residence in time to understand the situation and make further arrangements; By sending a flashing light prompt through the reminder doorbell, passers-by can be alerted and asked for help; pedestrians can quickly press the emergency button clearly marked on the reminder doorbell. After the elderly see the request prompt on the smart bracelet, if they confirm to allow it, the built-in sensor of the reminder doorbell will immediately capture this button action, triggering the corresponding data collection and transmission process to open the door.

7. The method for early warning of abnormal activities of elderly people living at home according to claim 5, characterized in that: The unresponsive upgrade further includes: Identity verification: The service staff touches the doorbell with the NFC key, triggering the camera to capture the face image; Blockchain evidence storage: The facial image is compared with the service personnel's pre-recorded information, and the verification results are written into the blockchain node via fiber optic broadband; Unlock record: After successful verification, an unlock record is generated, which includes a timestamp, personnel ID, and real-time video footage transmitted by the 5G network slice.

8. A device for early warning of abnormal activities of elderly people at home, characterized in that: include: Smart bracelet module: acquires the elderly's heart rate, blood oxygen and motion acceleration data, and transmits them to the cloud analysis platform via Bluetooth; Doorbell module: acquires information data of service personnel and uploads the integrated data to the smart bracelet and cloud analysis platform via Bluetooth; NFC identity verification module: Linked with the doorbell camera, it verifies the service personnel's biometrics and connects to the blockchain evidence storage platform via fiber optic broadband; Cloud analysis module: acquires data information from the smart bracelet module and the doorbell module, and further cleans, classifies and stores it for executing any of the method steps described in claims 1-7.

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