Wi-Fi HaLow-based intelligent medical wrist strap device, real-time monitoring system and method

Abstract

The invention relates to the field of Internet of Things medical equipment, discloses an intelligent medical wrist strap device based on Wi-Fi Halow and a real-time monitoring system and method, and solves the problems that an existing intelligent wrist strap based on BLE is short in transmission distance, poor in through-wall performance, unstable in data transmission due to interference and poor in monitoring effect. And the requirements of real-time physical sign monitoring, accurate position management and full-scene stable data transmission of the patient by the hospital are difficult to meet. According to the scheme, when the wrist strap device is initially powered on, the wrist strap device is in a low-power-consumption standby mode, physiological information of a wearer and RSSI data of surrounding Wi-Fi hotspots are collected by periodically awakening a sampling module and a positioning module, and the physiological information and the RSSI data are uploaded to a server through a Wi-Fi Halow communication module; the wrist strap equipment enters the low-power-consumption mode again after completing data uploading; and the server compares the received physiological information with a preset threshold value, estimates the position of the wearer based on the RSSI data and a pre-established Wi-Fi fingerprint database, further judges whether sign abnormity and border crossing behavior abnormity occur or not, and pushes alarm information to the nurse station terminal when the sign abnormity and the border crossing behavior abnormity occur.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) medical devices, specifically to a smart medical wristband device, real-time monitoring system, and method based on Wi-Fi Halow. Background Technology

[0002] In healthcare settings such as hospitals and nursing homes, patient identification, vital sign monitoring, and location security management are core aspects of ensuring quality care and patient safety. Currently, hospitals widely use paper wristbands as the primary identification tool, but these only carry static information such as patient name, age, and medical record number. This requires manual verification by medical staff, which is not only inefficient but also unable to proactively collect vital sign data such as body temperature and heart rate, nor does it offer location tracking capabilities. When dealing with postoperative patients requiring close monitoring, elderly people with dementia, or individuals with mobility impairments, paper wristbands are insufficient to meet the management needs of real-time monitoring of patient health status and preventing them from wandering off or leaving the care area. This results in delayed nursing response and inadequate safety risk control.

[0003] To overcome the functional limitations of paper wristbands, smart wristband solutions based on BLE (Bluetooth Low Energy) technology have gradually emerged in the industry. While these solutions can achieve basic vital sign data collection and short-range data transmission, they suffer from certain drawbacks in the complex environment of hospitals due to the inherent characteristics of BLE technology. Firstly, the transmission distance is short (usually the effective distance is no more than 10 meters) and the wall penetration performance is poor. When patients move in different areas such as wards and corridors, data transmission is easily interrupted due to signal blockage.

[0004] Secondly, hospitals contain a large number of medical devices (such as monitors and ultrasound equipment) and wireless signals (such as traditional Wi-Fi and Bluetooth devices). BLE signals are easily interfered with, causing data packet loss and unstable transmission, which affects the real-time performance and accuracy of vital signs data.

[0005] Third, BLE technology is not directly compatible with the IP protocol and requires the deployment of an additional gateway for protocol conversion, which increases the system deployment cost and complexity, making it difficult to adapt to the large-scale deployment needs of hospitals with intensive intelligent devices.

[0006] With the development of IoT medical technology, hospitals have higher requirements for the low power consumption, long range, high stability, and strong compatibility of smart nursing devices: on the one hand, the wristband devices worn by patients need to have long battery life to avoid frequent charging affecting use; on the other hand, the system needs to cover all scenarios such as wards, corridors, and elevators to ensure data transmission without dead zones, while being compatible with the hospital's existing local area network architecture to reduce the difficulty of transformation.

[0007] Wi-Fi HaLow (IEEE 802.11ah) technology, as a wireless communication standard optimized for IoT scenarios, has the advantages of low power consumption, long-distance communication, strong wall penetration capability, and native IP protocol compatibility. It can effectively solve the transmission limitations of BLE solutions in medical scenarios, while meeting the needs of dense device deployment. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to provide a smart medical wristband device, real-time monitoring system and method based on Wi-Fi Halow, which solves the problems of short transmission distance, poor wall penetration performance and susceptibility to interference leading to unstable data transmission in existing BLE-based smart wristbands, making it difficult to meet the hospital's needs for real-time monitoring of patients' vital signs, accurate location management and stable data transmission in all scenarios.

[0009] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows: In a first aspect, the present invention provides a smart medical wristband device based on Wi-Fi HaLow, comprising: The main control module is used to coordinate and control the operation of various functional modules; The Wi-Fi HaLow communication module is electrically connected to the main control module and is used to establish communication with the Wi-Fi HaLow gateway inside the hospital and upload the collected data to the hospital's local area network server. The physiological monitoring module is electrically connected to the main control module and is used to monitor the wearer's physiological data in real time. The fall detection module is electrically connected to the main control module and is used to monitor the wearer's fall movements in real time. The positioning module, integrated into the Wi-Fi HaLow communication module, is used to scan surrounding Wi-Fi network hotspots, collect the received signal strength of each hotspot, and combine it with the hospital's preset Wi-Fi fingerprint database to achieve coarse-grained positioning. The power module is electrically connected to the main control module, the Wi-Fi HaLow communication module, the physiological monitoring module, and the positioning module respectively to provide power support.

[0010] Furthermore, the physiological monitoring module includes, but is not limited to: The body temperature detection module is used to measure the wearer's body surface temperature data in real time; The heart rate detection module is used to monitor the wearer's heart rate data in real time; The blood oxygen detection module is used to monitor the wearer's blood oxygen concentration data in real time; The blood pressure monitoring module is used to monitor the wearer's blood pressure data in real time.

[0011] Furthermore, the main control module is also used to perform anomaly judgment: based on the detected physiological data and preset thresholds, it determines whether the physiological signs are abnormal; based on the fall action detection results, it determines whether the wearer has fallen; when the physiological signs are abnormal or a fall occurs, it triggers the Wi-Fi HaLow communication module to perform emergency data upload.

[0012] Furthermore, the power module supports wireless charging or standard interface charging, and the main control module is also used to dynamically adjust the data acquisition frequency and upload frequency according to the remaining battery power.

[0013] Secondly, the present invention also provides a smart medical real-time monitoring system based on Wi-Fi HaLow, which includes the aforementioned smart medical wristband device based on Wi-Fi HaLow; and further includes: Multiple Wi-Fi HaLow gateways are deployed in key areas of hospital wards, corridors, and entrances to establish wireless connections with the Wi-Fi HaLow communication module of the smart medical wristband device. The hospital's local area network server is communicatively connected to the multiple Wi-Fi HaLow gateways. It is used to receive, store, and process the physiological monitoring data and location data uploaded by the smart medical wristband device, establish the wearer's data profile, and preset abnormal alarm conditions. The nurse station terminal is connected to the hospital's local area network server to display the wearer's vital signs data and location information in real time, receive abnormal alarm information pushed by the hospital's local area network server, and record alarm logs.

[0014] Furthermore, the hospital LAN server is also used to: construct a hospital Wi-Fi fingerprint database, which is generated by collecting Wi-Fi hotspot RSSI values ​​at various reference points in the hospital using a mobile debugging device; the hospital LAN server uses an RSSI fingerprint matching algorithm to match the RSSI data uploaded by the smart medical wristband device with the Wi-Fi fingerprint database to calculate the wearer's estimated location.

[0015] Furthermore, the abnormal alarms include, but are not limited to: alarms caused by abnormal physiological parameters, alarms caused by fall detection, alarms caused by removal of the wristband device, alarms caused by low battery of the wristband device, and alarms caused by removal of the wristband.

[0016] Thirdly, the present invention also provides a smart medical real-time monitoring method based on Wi-Fi HaLow, applied to the aforementioned real-time monitoring system, the method comprising the following steps: S1. The smart medical wristband device enters low-power mode after power-on; S2. The physiological monitoring module is activated periodically or as needed to collect physiological data; S3. Cache the collected physiological data and wake up the Wi-Fi HaLow communication module; S4. Connect to the nearest Wi-Fi HaLow gateway via the Wi-Fi HaLow communication module, package the cached data and upload it to the hospital's local area network server; S5. The positioning module scans surrounding Wi-Fi hotspots and collects RSSI data, which is then uploaded to the hospital's local area network server via the Wi-Fi HaLow communication module; S6. After completing the data upload, the smart medical wristband device re-enters low-power mode; S7. The hospital LAN server calculates the wearer's estimated location based on the received RSSI data and the Wi-Fi fingerprint database, and determines whether the wearer has deviated from the authorized area. If so, it pushes an out-of-bounds alarm to the nurse station terminal. S8. The hospital's local area network server determines whether the physiological data exceeds the preset threshold. If so, it pushes an alarm for abnormal physiological signs to the nurse station terminal. Furthermore, in step S2, the timed wake-up of the physiological monitoring module is achieved by waking up the physiological monitoring module when the preset period arrives; step S3 also includes: the main control module compares the collected physiological data with a preset threshold, and triggers an emergency alarm when the preset threshold is exceeded.

[0017] Furthermore, in step S7, the boundary crossing alarm includes: a pop-up notification on the nurse station terminal, activation of the audible and visual alarm, and logging of the boundary crossing by the backend system.

[0018] The beneficial effects of this invention are: (1) Breaking through the limitations of traditional wristband functions, achieving multi-dimensional intelligent monitoring: Compared to paper wristbands that can only passively identify patients, this invention integrates a physiological monitoring module that can collect patients' vital signs data in real time or periodically. At the same time, it combines a positioning module to achieve patient location tracking, upgrading static identification to dynamic monitoring of vital signs and location. This meets the core needs of hospitals for real-time patient monitoring and safety management, and effectively fills the technological gap in traditional wristbands that cannot actively acquire key nursing data.

[0019] (2) Address the shortcomings of existing wireless communication and ensure data transmission stability: To address the issues of short transmission distance, poor wall penetration, and susceptibility to interference in BLE-based smart wristbands, this invention employs Wi-Fi HaLow technology. Leveraging the characteristics of sub-1GHz frequency bands, it achieves long-distance, strong wall-penetrating wireless communication and is natively compatible with the IP protocol, allowing access to the hospital's local area network without additional protocol conversion. In the complex electromagnetic environment of a hospital, it effectively resists interference from medical devices and other wireless signals, reducing data packet loss and transmission interruptions, ensuring stable uploading of critical data such as vital signs and location, and providing reliable data support for real-time nursing decisions.

[0020] (3) Low power consumption design extends device battery life and is suitable for long-term wear: The power module, in conjunction with the main control module, employs a low-power control strategy. During non-working cycles, only low-power sampling is maintained, while the positioning module and Wi-Fi HaLow communication module go into sleep mode, waking up only when data is uploaded or an abnormality is triggered, significantly reducing energy consumption. It also supports rechargeable batteries and dynamically adjusts the acquisition / upload frequency, ensuring that the device can operate continuously for a long time, reducing the maintenance workload of frequent charging for medical staff, and adapting to the needs of 24-hour patient monitoring.

[0021] (4) Combining precise positioning with tiered alarms enhances patient safety: By constructing a hospital WiFi fingerprint database and combining it with the RSSI fingerprint matching algorithm to achieve coarse-grained patient positioning, it is possible to accurately determine whether a patient has deviated from the authorized care area. Alarm mechanisms are designed for different abnormal scenarios such as abnormal vital signs, boundary crossing, wristband removal, and falls, so as to achieve rapid response and intervention in abnormal situations. Attached Figure Description

[0022] Figure 1 This is a structural block diagram of a smart medical wristband device based on Wi-Fi HaLow in an embodiment of the present invention.

[0023] Figure 2 This is a block diagram of the intelligent medical real-time monitoring system based on Wi-Fi HaLow in an embodiment of the present invention.

[0024] Figure 3 This is a flowchart of the intelligent medical real-time monitoring method based on Wi-Fi HaLow in an embodiment of the present invention. Detailed Implementation

[0025] This invention aims to provide a smart medical wristband device, real-time monitoring system, and method based on Wi-Fi Halow, addressing the problems of existing BLE-based smart wristbands, such as short transmission distance, poor wall penetration, and susceptibility to interference leading to unstable data transmission, which fail to meet the needs of hospitals for real-time patient vital sign monitoring, precise location management, and stable data transmission across all scenarios. The core idea is: at the hardware level, a medical wristband integrating multiple modules is designed: a low-power main control module serves as the core coordination hub, linking with a physiological monitoring module to collect vital sign data in real time; a positioning module integrated into the Wi-Fi HaLow communication module achieves coarse positioning; and a power module with a rechargeable battery and dynamic power management ensures long-term device battery life.

[0026] At the system level, a hierarchical architecture is established: wristband device - Wi-Fi HaLow gateway - hospital LAN server - nurse station terminal. The wristband establishes stable, long-distance, and interference-resistant communication with the gateway through Wi-Fi HaLow technology and uploads data to the server. The server pre-builds a hospital Wi-Fi fingerprint database, calculates the patient's location through the RSSI fingerprint matching algorithm, and stores and analyzes vital signs and location data. The nurse station terminal displays data in real time and receives abnormal alarms (boundary crossing, abnormal vital signs, etc.).

[0027] At the application logic level, a low-power loop + anomaly priority operation mechanism is formed: under normal conditions, the module is woken up according to the preset cycle to collect vital signs and cache and upload them. During non-working periods, only the core module's low-power sampling is retained; the location determination is achieved by the server comparing the patient's location with the authorized area; when the user's vital signs or location are abnormal, an emergency upload is triggered, and an alarm is pushed to the nurse station simultaneously, thereby realizing rapid response and intervention in abnormal situations.

[0028] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0029] This embodiment first provides a smart medical wristband device based on Wi-Fi HaLow, see [link to documentation]. Figure 1 It includes: The main control module is used to coordinate and control the operation of various functional modules. In an exemplary implementation, a low-power microcontroller can be used to control and manage the overall device, including sensor data acquisition, communication scheduling, power management, anomaly detection and response processing, etc.

[0030] The Wi-Fi HaLow communication module is electrically connected to the main control module and is used to establish communication with the Wi-Fi HaLow gateway inside the hospital, uploading the collected data to the hospital's local area network server. The Wi-Fi HaLow communication module is a communication module based on the IEEE 802.11ah protocol, which can perform long-distance, low-power wireless communication in the frequency band below 1 GHz. It connects to the Wi-Fi HaLow gateway deployed inside the hospital and can communicate with the server in the hospital through the TCP / IP protocol or the MQTT protocol.

[0031] A physiological monitoring module, electrically connected to the main control module, is used to monitor the wearer's physiological data in real time. In an exemplary embodiment, the physiological monitoring module may include: a body temperature detection module for real-time measurement of the wearer's body surface temperature data, such as using a high-precision digital body temperature sensor fixed inside the wristband to collect the wearer's body surface temperature data in real time or periodically; a heart rate detection module for real-time monitoring of the wearer's heart rate data, such as using an integrated photoplethysmography (PPG) sensor to obtain heart rate data by detecting changes in blood flow; a blood oxygen detection module for real-time monitoring of the wearer's blood oxygen concentration data, such as using an SpO2 sensor; and a blood pressure detection module for real-time monitoring of the wearer's blood pressure data. It is understood that the physiological monitoring module can be expanded according to actual needs and is not limited to the above-mentioned detection modules.

[0032] The fall detection module is electrically connected to the main control module and is used to monitor the wearer's fall movements in real time; in an exemplary implementation, a three-axis accelerometer can be used to achieve fall detection.

[0033] The positioning module, integrated into the Wi-Fi HaLow communication module, is used to scan surrounding Wi-Fi network hotspots, collect the received signal strength of each hotspot, and combine it with the hospital's preset Wi-Fi fingerprint database to achieve coarse-grained positioning.

[0034] The power module is electrically connected to the main control module, Wi-Fi HaLow communication module, physiological monitoring module, and positioning module to provide power support. It includes a rechargeable lithium battery and a power management chip, supporting low-power standby and fast charging management. The main control module can also dynamically adjust the data acquisition and upload frequency based on the remaining battery power to extend battery life.

[0035] Based on the aforementioned intelligent medical wristband device, this embodiment also provides an intelligent medical real-time monitoring system based on Wi-Fi HaLow, see [link to documentation]. Figure 2 It includes the aforementioned intelligent medical wristband device, and also includes: Multiple Wi-Fi HaLow gateways are deployed in key areas of the hospital, such as wards, corridors, and entrances, to establish wireless connections with the Wi-Fi HaLow communication module of the smart medical wristband device.

[0036] The hospital's local area network server communicates with the multiple Wi-Fi HaLow gateways to receive, store, and process physiological monitoring data and location data uploaded by the smart medical wristband device, establish a data profile for the wearer, and preset abnormal alarm conditions.

[0037] The nurse station terminal is connected to the hospital's local area network server to display the wearer's vital signs data and location information in real time, receive abnormal alarm information pushed by the hospital's local area network server, and record alarm logs.

[0038] The working principle of the wristband device for the above monitoring system includes: Routine monitoring: The wristband collects basic vital signs data such as body temperature and heart rate at regular intervals (e.g., every 5 minutes) and caches the data in the local storage area.

[0039] Data Upload: After each data collection, the Wi-Fi HaLow module is woken up, connects to the nearest gateway, and packages and uploads the cached data to the server.

[0040] Anomaly detection: The main control module monitors vital signs parameters in real time. If abnormal body temperature (e.g., above 38°C) or abnormal heart rate (e.g., below 50 beats / min or above 120 beats / min) is detected, an emergency upload is immediately triggered and an alarm is pushed to the nurse station system.

[0041] Location and Area Monitoring: The wristband periodically scans for nearby WiFi hotspots to determine if the user is within an authorized area. If it detects that the user has left a designated area (such as a ward or nursing area), it immediately reports the departure event and sends location information.

[0042] Low power management: During non-working cycles, the fall detection module is in a low power sampling state, while the physiological monitoring module, positioning module, and Wi-Fi HaLow module are in a sleep state, only waking up when data is uploaded or an anomaly occurs, maximizing battery life.

[0043] Charging and maintenance: The wristband supports wireless charging or charging via a standard interface, allowing healthcare professionals to periodically check the battery level and perform charging maintenance.

[0044] The server-side functions of the aforementioned monitoring system include: It receives body temperature, heart rate, and location data uploaded from each wristband.

[0045] Establish patient data files and display them in real time at the nurse station terminal.

[0046] Set alarm conditions and send them to designated medical staff.

[0047] It supports functions such as historical data query, statistical analysis, and abnormal trend prediction.

[0048] Initialize and construct a hospital map to form a Wi-Fi fingerprint database.

[0049] Receive location data reported by the wristband.

[0050] The location of the corresponding patient is analyzed and displayed at the nurses' station.

[0051] Before the implementation of the solution, multiple Wi-Fi HaLow hotspots were deployed in key areas such as wards, corridors, and entrances and exits. WiFi RSSI values ​​were collected at multiple reference points using mobile devices (such as adjustment wristbands) to form a Wi-Fi fingerprint database. The fingerprint database includes the average and standard deviation of the RSSI of multiple WiFi hotspots corresponding to each reference point.

[0052] After deployment, the medical wristband worn by the patient scans and uploads the RSSI values ​​of nearby Wi-Fi HaLow hotspots every 30 seconds. If the system detects that the patient's current location is no longer within their ward or permitted activity area (such as the end of a corridor or restroom), but near the ward exit area, the system immediately sends an out-of-bounds alarm. The nursing station receives the alert and intervenes to ensure patient safety. Furthermore, the server compares the physiological monitoring data uploaded by the wristband device with preset thresholds; if the threshold is exceeded, an alarm is triggered immediately.

[0053] Based on the aforementioned monitoring system, this embodiment also provides a smart medical real-time monitoring method based on Wi-Fi HaLow, see [link to documentation]. Figure 3 It includes the following steps: S1. The smart medical wristband device enters low-power mode after power-on.

[0054] In this step, after the medical wristband device is powered on, the main control module first completes initialization (such as loading preset parameters and detecting the hardware status of each module), and then performs low-power mode control: For non-real-time core modules (Wi-Fi HaLow communication module, positioning module), their core functional circuits (such as radio frequency unit, scanning unit) are directly shut down, and only the wake-up signal connection with the main control module is retained, and they enter deep sleep standby.

[0055] For real-time sensing modules (such as fall detection modules and wearing status detection modules), a low-power monitoring mode can be switched to, for example, by appropriately reducing the sampling frequency, so as to ensure real-time sensing capabilities while avoiding high energy consumption.

[0056] For the physiological monitoring module, the sampling function is temporarily not activated. Only timed wake-up triggers or specific triggers (such as triggers via buttons or remote control) are retained. Wake-up sampling is only performed after the trigger is activated. At this time, the module power consumption is close to the sleep level.

[0057] The device quickly enters a low-power state after startup, avoiding unnecessary energy consumption in the early stages of power-on and laying the foundation for long-term battery life.

[0058] S2. The physiological monitoring module is woken up periodically or as needed to collect physiological data.

[0059] In this step, for routine timed wake-up: the main control module sends a wake-up signal to the physiological monitoring module according to a preset period (such as 1-5 minutes, which can be adjusted by the hospital according to the patient's care level, for example, 1 minute for critically ill patients after surgery and 5 minutes for ordinary patients). After the module is woken up, it starts sampling.

[0060] For on-demand wake-up for abnormalities: When a real-time sensing module (such as a fall detection module) detects an abnormal action (such as a sudden change in acceleration suspected of being a fall), the main control module will immediately trigger an emergency wake-up of the physiological monitoring module, adding an extra physiological data collection (such as synchronously detecting changes in the patient's heart rate after a fall), providing more comprehensive data support for subsequent abnormality determination; after sampling is completed, the high-power sampling unit is automatically turned off, and only the low-power standby wake-up trigger function is retained, waiting for the next wake-up command.

[0061] S3. Cache the collected physiological data and wake up the Wi-Fi HaLow communication module.

[0062] In this step, the main control module stores the body temperature, heart rate and other data (with collection timestamp and wristband device ID) collected by the physiological monitoring module into a local non-volatile temporary buffer (such as EEPROM) to avoid data loss due to subsequent communication interruption. At the same time, the buffer adopts a first-in-first-out mechanism. If the cached data reaches a preset threshold, the communication module will be woken up in advance even if the next upload cycle has not arrived to prevent data overflow.

[0063] After the main control module sends a wake-up signal to the Wi-Fi HaLow communication module, the Wi-Fi HaLow communication module starts up and first completes a pre-scan: quickly detects the signal strength RSSI value of surrounding Wi-Fi HaLow gateways, selects the gateway with the strongest signal, and then enters the waiting state; if no available gateway is found in the first scan, the module will rescan at a certain interval (e.g., 30 seconds). If no available gateway is found after multiple scans, it will report communication abnormality information to the main control module. The main control module will temporarily store the data in the buffer area to avoid energy waste caused by long-term scanning.

[0064] S4. Connect to the nearest Wi-Fi HaLow gateway via the Wi-Fi HaLow communication module, and upload the cached data to the hospital's local area network server.

[0065] In this step, the Wi-Fi HaLow communication module completes identity authentication (verifying whether the wristband device ID is in the hospital's authorized list) based on the nearest selected gateway using the hospital's preset encryption protocol. After successful authentication, a TCP / IP connection or MQTT protocol connection is established. Next, the main control module packages the physiological data in the buffer and sends it to the gateway through the Wi-Fi HaLow communication module. After receiving the data, the gateway automatically forwards it to the hospital's local area network server. During the upload process, a data verification mechanism is used. If the server detects a data verification failure, it will send a retransmission command to the wristband device, and the communication module will re-upload the corresponding data. When the communication module receives a confirmation signal from the server that the data has been successfully received, it sends feedback to the main control module that the upload is complete. The main control module immediately clears the uploaded data in its local temporary buffer. If multiple retransmissions still fail, the data will continue to be retained in the buffer, waiting for the next time the communication module is woken up to try uploading again.

[0066] S5. The positioning module scans surrounding Wi-Fi hotspots and collects RSSI data, which is then uploaded to the hospital's local area network server via the Wi-Fi HaLow communication module.

[0067] In this step, after being woken up, the positioning module scans the deployed Wi-Fi HaLow hotspots in the hospital (scanning at least 3 hotspots to ensure positioning accuracy), records the RSSI value and MAC address of each hotspot, and filters out invalid data with weak signal strength, retaining only the RSSI information of valid hotspots to reduce the redundancy of subsequent server matching calculations.

[0068] S6. After completing the data upload, the smart medical wristband device re-enters low-power mode.

[0069] In this step, after the Wi-Fi HaLow communication module completes the data upload and receives the upload confirmation from the server, the main control module in the wristband device controls the device to re-enter the low-power mode. The specific control of the low-power mode is as described in step S1.

[0070] S7. The hospital's local area network server calculates the wearer's estimated location based on the received RSSI data and the Wi-Fi fingerprint database, and determines whether the wearer has deviated from the authorized area. If so, it pushes an out-of-bounds alarm to the nurse station terminal.

[0071] In this step, the server first calls the preset Wi-Fi fingerprint database and uses the K-Nearest Neighbors (KNN) algorithm to calculate the similarity between the RSSI data uploaded by the wristband device and the RSSI data of each reference point in the database. The top 3 reference points with the highest similarity are selected, and the wearer's final location estimate is calculated by weighted average.

[0072] The server calls the "Patient Authorized Area Configuration Table" (preset by the hospital according to patient type, such as the authorized area for postoperative patients being the ward + corridor, and the authorized area for dementia patients being the ward only) to determine whether the estimated location falls within the authorized area. If the estimated location exceeds the authorized area (e.g., the patient is near the ward exit or enters a prohibited area), or if the location results show movement towards an unauthorized area three times consecutively, it is determined to be an "out-of-bounds" error. The server immediately generates an "out-of-bounds alarm message" (including patient ID, wristband device ID, current location, and out-of-bounds time), pushes it to the nurse station terminal (e.g., large screen display, terminal pop-up) via the hospital's local area network, and simultaneously sends it to the mobile terminal of the medical staff responsible for the patient (e.g., mobile APP push). In addition, the server automatically stores the alarm information in the alarm log database for subsequent traceability and statistics.

[0073] S8. The hospital's local area network server determines whether the physiological data exceeds the preset threshold. If so, it pushes an alarm for abnormal physiological signs to the nurse station terminal.

[0074] In this step, the server first associates the corresponding "patient care record" with the wristband device ID and calls the patient's "personalized physiological threshold" (e.g., the normal heart rate range for elderly patients is set to 50-100 beats / min, and for children it is set to 80-120 beats / min). If the patient does not have a personalized threshold (e.g., a patient undergoing a routine health check), the hospital's preset "general medical threshold" is used (e.g., a body temperature > 38.5℃ is abnormal, and a heart rate < 50 beats / min or > 120 beats / min is abnormal).

[0075] Next, the server compares the received physiological data (body temperature, heart rate) with the corresponding thresholds. If the received physiological data exceeds the threshold, it is determined to be an abnormal physiological sign. At the same time, the server will combine the patient's historical data (such as the body temperature change trend in the past 24 hours). If the data shows a rapid upward / downward trend (such as the body temperature rising from 37°C to 38.2°C in 1 hour), even if it does not exceed the threshold, it will trigger an "abnormal trend alarm".

[0076] Based on the severity of the anomaly, the server categorizes alarms into "emergency alarms" (such as body temperature > 39℃, heart rate < 40 beats / min) and "normal alarms". Emergency alarms will trigger audible and visual alarms on the nurse station terminal (such as a buzzer sounding and an alarm light flashing) and will be pushed to the on-duty doctor's terminal first. Normal alarms will only be displayed in a pop-up window on the nurse station terminal and will be handled by nurses according to their priority.

[0077] Although embodiments of the present invention have been described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present invention, and all such changes and alterations shall not depart from the protection scope of the present invention.

Claims

1. A smart medical wristband device based on Wi-Fi HaLow, characterized in that, include: The main control module is used to coordinate and control the operation of various functional modules; The Wi-Fi HaLow communication module is electrically connected to the main control module and is used to establish communication with the Wi-Fi HaLow gateway inside the hospital and upload the collected data to the hospital's local area network server. The physiological monitoring module is electrically connected to the main control module and is used to monitor the wearer's physiological data in real time. The fall detection module is electrically connected to the main control module and is used to monitor the wearer's fall movements in real time. The positioning module, integrated into the Wi-Fi HaLow communication module, is used to scan surrounding Wi-Fi network hotspots, collect the received signal strength of each hotspot, and combine it with the hospital's preset Wi-Fi fingerprint database to achieve coarse-grained positioning. The power module is electrically connected to the main control module, the Wi-Fi HaLow communication module, the physiological monitoring module, and the positioning module respectively to provide power support.

2. The smart medical wristband device based on Wi-Fi HaLow as described in claim 1, characterized in that, The physiological monitoring module includes: The body temperature detection module is used to measure the wearer's body surface temperature data in real time; The heart rate detection module is used to monitor the wearer's heart rate data in real time; The blood oxygen detection module is used to monitor the wearer's blood oxygen concentration data in real time; The blood pressure monitoring module is used to monitor the wearer's blood pressure data in real time.

3. The smart medical wristband device based on Wi-Fi HaLow as described in claim 1, characterized in that, The main control module is also used to perform anomaly judgment: based on the detected physiological data and preset thresholds, it determines whether the physiological signs are abnormal; based on the fall action detection results, it determines whether the wearer has fallen; when the physiological signs are abnormal or a fall occurs, it triggers the Wi-Fi HaLow communication module to perform emergency data upload.

4. The smart medical wristband device based on Wi-Fi HaLow as described in claim 1, characterized in that, The power module supports wireless charging or standard interface charging, and the main control module is also used to dynamically adjust the data acquisition frequency and upload frequency according to the remaining battery power.

5. A smart medical real-time monitoring system based on Wi-Fi HaLow, comprising a smart medical wristband device based on Wi-Fi HaLow as described in any one of claims 1-4, characterized in that, Also includes: Multiple Wi-Fi HaLow gateways are deployed in key areas of hospital wards, corridors, and entrances to establish wireless connections with the Wi-Fi HaLow communication module of the smart medical wristband device. The hospital's local area network server is communicatively connected to the multiple Wi-Fi HaLow gateways. It is used to receive, store, and process the physiological monitoring data and location data uploaded by the smart medical wristband device, establish the wearer's data profile, and preset abnormal alarm conditions. The nurse station terminal is connected to the hospital's local area network server to display the wearer's vital signs data and location information in real time, receive abnormal alarm information pushed by the hospital's local area network server, and record alarm logs.

6. The intelligent medical real-time monitoring system based on Wi-Fi HaLow as described in claim 5, characterized in that, The hospital LAN server is also used to: construct a hospital Wi-Fi fingerprint database, which is generated by collecting Wi-Fi hotspot RSSI values ​​at various reference points in the hospital using a mobile debugging device; the hospital LAN server uses an RSSI fingerprint matching algorithm to match the RSSI data uploaded by the smart medical wristband device with the Wi-Fi fingerprint database to calculate the wearer's location estimate.

7. The intelligent medical real-time monitoring system based on Wi-Fi HaLow as described in claim 5, characterized in that, The abnormal alarms include: alarms caused by abnormal physiological parameters, alarms caused by fall detection, alarms caused by removal of the wristband device, alarms caused by low battery of the wristband device, and alarms caused by removal of the wristband.

8. A Wi-Fi HaLow-based intelligent medical real-time monitoring method, applied to a Wi-Fi HaLow-based intelligent medical real-time monitoring system as described in any one of claims 5-7, characterized in that, The method includes the following steps: S1. The smart medical wristband device enters low-power mode after power-on; S2. The physiological monitoring module is activated periodically or as needed to collect physiological data; S3. Cache the collected physiological data and wake up the Wi-Fi HaLow communication module; S4. Connect to the nearest Wi-Fi HaLow gateway via the Wi-Fi HaLow communication module, package the cached data and upload it to the hospital's local area network server; S5. The positioning module scans surrounding Wi-Fi hotspots and collects RSSI data, which is then uploaded to the hospital's local area network server via the Wi-Fi HaLow communication module; S6. After completing the data upload, the smart medical wristband device re-enters low-power mode; S7. The hospital LAN server calculates the wearer's estimated location based on the received RSSI data and the Wi-Fi fingerprint database, and determines whether the wearer has deviated from the authorized area. If so, it pushes an out-of-bounds alarm to the nurse station terminal. S8. The hospital's local area network server determines whether the physiological data exceeds the preset threshold. If so, it pushes an alarm for abnormal physiological signs to the nurse station terminal.

9. The intelligent medical real-time monitoring method based on Wi-Fi HaLow as described in claim 8, characterized in that, In step S2, the timed wake-up physiological monitoring module is activated by a preset period when the period arrives. Step S3 also includes: the main control module compares the collected physiological data with a preset threshold, and triggers an emergency alarm when the preset threshold is exceeded.

10. The intelligent medical real-time monitoring method based on Wi-Fi HaLow as described in claim 8, characterized in that, In step S7, the boundary crossing alarm includes: a pop-up notification on the nurse station terminal, activation of the audible and visual alarm, and logging of the boundary crossing by the backend system.

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