A medical instrument state management system based on internet of things technology

Abstract

The application discloses a medical instrument state management system based on an internet of things technology, and has the characteristics that a sensing layer is arranged on a medical instrument body, a network layer is connected with the sensing layer, a management layer is arranged on a cloud server and is in communication connection with the network layer and is used for receiving and processing the multiple state data.The medical instrument state management system based on the internet of things technology can realize full-time and space sensing of the running state of the medical instrument, real-time transmission and intelligent analysis of data, and compared with a traditional manual or passive management mode, can realize real-time acquisition of equipment parameters through a sensor, can enable medical staff to master the equipment use condition at any time, can realize accurate tracking of the equipment through RFID / two-dimensional code combination and wireless positioning, can reduce the equipment failure rate and prolong the service life through big data analysis and predictive maintenance, can provide an intuitive Web management interface, can simplify the management process and can improve the management efficiency.

Description

Technical Field

[0001] This invention relates to the field of medical device management technology, and in particular to a medical device status management system based on Internet of Things (IoT) technology. Background Technology

[0002] With the expansion of hospitals and the proliferation of medical devices, traditional medical device management methods can no longer meet the needs of refined management throughout the entire equipment lifecycle. Research on IoT-based medical device monitoring systems has been conducted both domestically and internationally. For example, IoT-based medical device status monitoring solutions use a wireless sensor network composed of terminal sensors, routers, and coordinators to achieve real-time monitoring of equipment power-on / off status, operating sounds, and environmental parameters. Other research indicates that applying IoT technology to medical device status monitoring systems can enable the analysis and handling of potential equipment failures by adding data acquisition, transmission, and alarm sensors. Furthermore, IoT applications for specific scenarios, such as wireless infusion monitoring systems, have achieved real-time monitoring and closed-loop management of infusion drip rates through IoT sensing technology. However, current technology still lacks a unified platform that can integrate equipment location, operating status, environmental monitoring, and predictive maintenance.

[0003] Therefore, it is necessary to provide a new medical device status management system based on Internet of Things (IoT) technology to solve the above-mentioned technical problems. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a medical device status management system based on Internet of Things (IoT) technology.

[0005] This invention provides a medical device status management system based on Internet of Things (IoT) technology, comprising: A sensing layer, disposed on the body of the medical device, is used to collect multi-dimensional status data of the medical device; the sensing layer includes: The unique identification and positioning module is used to provide a unique identifier for medical devices and enable spatial positioning. The environmental sensing module is used to collect environmental parameters of the environment in which the medical device is located. The operation sensing module is used to collect the operating parameters of the medical device itself; The network layer, connected to the perception layer, includes a wireless communication module for building a wireless sensor network and receiving and transmitting multi-dimensional state data collected by the perception layer. The management layer, deployed on a cloud server and communicatively connected to the network layer, is used to receive and process the diverse state data; the management layer includes: The data processing module is used to clean and store the received multi-state data; The status analysis module is used to generate and display real-time status information of medical devices based on the processed data. The predictive maintenance module is used to predict potential failures of medical devices based on historical status data.

[0006] Preferably, the unique identification and positioning module includes an RFID tag or a QR code module for unique identification of the medical device; the network layer or management layer dynamically tracks the medical device based on the received signal strength indication (RSSI) or time-of-flight (ToF) positioning algorithm, combined with the information from the unique identification and positioning module, to determine the room or bed location where the medical device is located.

[0007] Preferably, the network layer uses a dedicated IoT wireless platform that supports multi-device network management for data transmission; the platform is configured to maintain stable transmission quality in medical environments with wireless interference and to achieve data interface with hospital information systems (HIS) or mobile nursing systems (MCS).

[0008] Preferably, the management layer also includes a rule-based alarm system. The alarm system has preset parameter thresholds related to medical devices. When the monitored device parameters exceed the preset thresholds, it automatically pushes alarm information to the associated mobile terminal and records alarm logs.

[0009] Preferably, the predictive maintenance module has a built-in trained machine learning algorithm model. The model is trained based on historical fault data and corresponding operating parameters to output prediction results of potential equipment faults and automatically generate maintenance work orders based on the prediction results.

[0010] Preferably, the environmental sensing module includes a temperature and humidity sensor and / or a vibration sensor for real-time monitoring of temperature and humidity parameters around the medical device, and the state analysis module evaluates the impact of the environmental parameters on the device performance.

[0011] Preferably, the management layer also includes a full lifecycle management module, which records and manages the data of the entire process of medical devices from procurement, warehousing, allocation, use, maintenance to disposal, forming traceable and auditable electronic files.

[0012] Preferably, the operation sensing module includes a sound sensor and / or a current sensor; the status analysis module determines whether the medical device is in normal working condition by analyzing the device operation sound characteristics collected by the sound sensor or by analyzing the current waveform collected by the current sensor.

[0013] Preferably, the status analysis module provides a web-based visualization interface for graphically displaying the real-time operating status, geographical location information, and environmental parameters of medical devices, and supports retrieval by device type, department, or operating status.

[0014] Preferably, the wireless communication module includes a low-power wide-area network (LPWAN) module, a Wi-Fi module, or a 5G communication module, used to construct a wireless sensor network including a router and a coordinator to transmit data to a back-end server in real time.

[0015] Compared with related technologies, the medical device status management system based on Internet of Things technology provided by this invention has the following beneficial effects: This invention provides a medical device status management system based on Internet of Things (IoT) technology, which realizes all-time and all-space perception of the operating status of medical devices, real-time data transmission, and intelligent analysis. Compared with traditional manual or passive management methods, it can collect equipment parameters in real time through sensors, allowing medical staff to keep track of equipment usage at any time. It can also achieve precise tracking of equipment through RFID / QR code combined with wireless positioning. Through big data analysis and predictive maintenance, it can reduce equipment failure rate, extend service life, and provide an intuitive web management interface to simplify management processes and improve management efficiency. Attached Figure Description

[0016] Figure 1 A schematic diagram of the structure of the medical device status management system based on Internet of Things technology provided by the present invention; Figure 2 This is a schematic diagram of the sensing layer structure provided by the present invention; Figure 3 A schematic diagram of the management structure provided for this invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions in the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings and specific examples. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0018] This embodiment provides a specific deployment and application example of a medical device status management system based on Internet of Things (IoT) technology in a hospital environment.

[0019] like Figures 1 to 3 As shown, this system includes: a perception layer, a network layer, and a management layer.

[0020] Sensing layer: Attached to the medical device that needs to be managed, it is responsible for collecting the device's own identity information, operating parameters, and surrounding environmental parameters.

[0021] Network layer: Composed of wireless access points and network coordinators deployed on each floor and in wards of the hospital, forming a wireless sensor network covering the entire hospital, responsible for securely and reliably transmitting the data collected by the perception layer to the management layer.

[0022] Management level: The software platform deployed on the hospital's private cloud or hosted cloud server is responsible for processing, analyzing, storing, and visualizing all received data, and providing advanced functions such as alarms and predictive maintenance.

[0023] In this embodiment, the configuration of the sensing layer varies slightly for different types of medical devices, but all include the following modules: Unique Identification and Positioning Module: Each piece of equipment, including large ventilators and CT scanners, and small infusion pumps and electrocardiogram monitors, has an ultra-high frequency passive RFID tag affixed to a prominent position on its body. The tag stores static information such as the equipment's unique identifier (UID), equipment type, brand and model, purchase date, and department to which it belongs. For frequently moved equipment, such as infusion pumps and patient monitors, a QR code is affixed to a fixed position on the equipment as a backup identification method, which can be scanned and confirmed by medical staff using a handheld terminal.

[0024] Environmental sensing module: Medical refrigerators storing reagents and high-precision biochemical analyzers are equipped with integrated environmental sensor nodes deployed inside or near them. These nodes include: Temperature and humidity sensor: Model SHT35, with an accuracy of ±0.3°C and ±1.5%RH, used for real-time monitoring of the temperature and humidity inside the equipment.

[0025] Vibration sensor: Model ADXL345 triaxial accelerometer, used to monitor whether equipment experiences abnormal vibration or displacement, especially for precision optical instruments or equipment in transit.

[0026] Running the sensing module: Configure it according to the device type. For power equipment (such as centrifuges, ventilators, and infusion pumps): connect a miniature non-invasive current sensor (such as the closed-loop Hall effect sensor ACS712) in parallel at its power input terminal to collect the operating current and voltage in real time at a sampling frequency of 100Hz, thereby calculating power consumption and analyzing the current waveform. At the same time, attach an electret condenser microphone near the motor or moving parts of the equipment as a sound sensor to collect the characteristic audio signals of the equipment during operation.

[0027] For non-powered equipment (such as hospital beds and wheelchairs): the movement and use of the equipment are determined by the reading frequency and signal strength changes of the RFID tags.

[0028] All perception layer modules adopt a low-power design and use an integrated microcontroller unit (MCU, model STM32L4 series) for initial data encapsulation and packaging, and then interact with the network layer communication module through the serial peripheral interface (SPI).

[0029] The network layer in this embodiment is built based on the LoRaWAN protocol and is deployed as follows: Wireless communication module: Each sensing layer node integrates a LoRa radio frequency module (model SX1278), which operates in the 470-510MHz frequency band. This module features low power consumption, strong penetration and long transmission distance.

[0030] Network Infrastructure: LoRa gateways (or concentrators, model RAK7249) are evenly deployed in the low-voltage rooms and ward corridor ceilings on each floor of the hospital. The gateways are connected to the hospital's intranet via Power over Ethernet (PoE). The gateways are responsible for receiving data uploaded by all sensing layer nodes within their coverage area and forwarding the data to the central network server via the IP network. The network server is equipped with LoRaNetworkServer software (such as ChirpStack), which is responsible for managing all network devices, including device network access authentication, data encryption and decryption, data duplicate frame removal, downlink command transmission, etc. The network platform has an adaptive data rate (ADR) function, which automatically adjusts the transmit power and data rate of each node according to the signal quality, effectively coping with multipath interference and signal attenuation in the complex environment of the hospital.

[0031] Data security and system integration: The network layer is logically isolated from the hospital's existing information systems by firewalls and gateways. The network server publishes the decrypted payload data to the intranet message queue via the MQTT (Message Queuing Telemetry Transport) protocol. The hospital information integration platform subscribes to this message queue to obtain device status data in real time. This system achieves seamless integration with the hospital's HIS and mobile nursing system (MCS). For example, when the MCS system performs an infusion operation for a patient, it can obtain the real-time flow rate and remaining volume data of the corresponding infusion pump from this system and automatically record it in the nursing record.

[0032] The management platform is deployed on the hospital's private cloud virtual server, adopting a Spring Boot microservice architecture and the time-series database InfluxDB. The platform includes the following core functional modules, which are implemented as follows: Data processing module: A real-time data stream processing pipeline based on Apache Kafka and Flink. The raw data stream first passes through a Kafka message queue for buffering and peak smoothing. Then, Flink tasks consume data from Kafka and perform the following operations: Data cleaning: Remove values ​​that are clearly outside the physical range (such as current > 100A), data packets with incorrect formats, and duplicate data reports.

[0033] Data completion: Convert the raw data reported by the device (such as the raw current ADC value) into the actual engineering unit value (such as milliampere mA) according to the calibration formula.

[0034] Data storage: The processed structured data is written to the InfluxDB time-series database by device ID and timestamp for efficient querying and analysis. At the same time, key event data (such as alarms and power on / off times) is stored in the relational database MySQL for easy auditing and report generation.

[0035] Status Analysis Module: Front-end interface: Provides a web-based visual interface developed based on the React framework. After logging in with an HTML5-enabled browser, users can see an overview dashboard of all the hospital's equipment. The dashboard area is an electronic map generated based on the hospital's actual CAD drawings. The map uses different colored icons (green - normal, yellow - caution, red - alarm, gray - offline) to intuitively display the location and status of each device.

[0036] Search Function: The left side of the interface provides a powerful multi-condition search panel. Users can select the device type (such as "infusion pump"), department (such as "ICU"), and current status (such as "offline") through the drop-down menu, or directly enter the device ID or model in the search box for precise search. The search results will be highlighted on the map.

[0037] Real-time details: Click on any device icon on the map to pop up a floating card with detailed information, displaying all its sensor data in real time, including: last reported time, real-time current / voltage waveform (trend of the most recent minute), ambient temperature and humidity, cumulative runtime, and a comprehensive health score derived from the data fusion algorithm.

[0038] Rule-based alarm system: Implemented using the Esper complex event processing engine, administrators can define alarm rules for different types of devices through a simple graphical configuration interface on the platform's backend. For example, configuring a rule for a medical refrigerator: "If the temperature > 8°C and the duration > 5 minutes, trigger an 'over-temperature alarm'." The system has a rich set of built-in rule templates, such as: overcurrent, voltage drop, excessive vibration, offline timeout, etc. Once the event engine detects that the rule conditions are met, it will immediately execute the following actions: Push notifications: Through the integrated push service, alarm information including device ID, location, anomaly value, and occurrence time will be sent to the mobile terminals of pre-bound responsible medical staff and maintenance engineers in the form of App notifications and SMS messages.

[0039] Log the alarm: Persist all details of the alarm event (including snapshot data at the time of triggering) to the alarm log table in the MySQL database for post-event analysis and accountability.

[0040] Predictive maintenance module: Data preparation: Extract historical data of a certain type of equipment (such as infusion pump) from the time series database, including normal operation data and data for a period of time before the failure. Each training data point contains multi-dimensional features: mean, variance, peak, and spectral energy of current; Mel frequency cepstral coefficients (MFCC) of sound; cumulative running time, ambient temperature and humidity, etc., and is labeled as whether the data point corresponds to a future failure.

[0041] Model Training: Using Python's Scikit-learn and TensorFlow libraries, a hybrid prediction model was built and trained. This model combines random forest (for handling structured features such as current statistics and runtime) and long short-term memory network LSTM (for handling temporal features such as current waveforms and temporal changes in sound signals). Through training with historical data, the model learns the characteristic patterns of the device's evolution from a healthy state to a faulty state.

[0042] Online prediction and work order generation: The trained model is packaged into a RESTful API service and deployed on the platform. Real-time data streams are sent to the API for real-time inference while entering the database. When the model outputs a fault probability for a certain device that exceeds a preset threshold (such as 70%), the platform automatically determines it as a "potential fault".

[0043] Integration with the work order system: The platform connects with the hospital's existing Enterprise Asset Management (EAM) system or a customized maintenance work order system via API calls. Once a potential fault is predicted, the system automatically creates a maintenance work order. The work order includes: equipment information, fault prediction type (e.g., "high probability of motor bearing wear"), confidence level, suggested inspection items (e.g., "check motor sound and current, clean bearing"), and recommended maintenance engineers (automatically assigned based on equipment type and department). After the work order is created, the engineer is notified via SMS and App, thus achieving closed-loop management from prediction to maintenance.

[0044] Full lifecycle management module: Using the unique ID of each device as the primary key, a full lifecycle electronic profile is created in the MySQL database. The profile content includes: Procurement and Warehousing: Record the purchase contract number, supplier, warehousing date, warranty expiration date, scanned copy of the original invoice, etc.

[0045] Allocation and Transfer: Record the department that uses the equipment, the location of use, the person in charge, and the time of transfer for each instance. This information is automatically updated by the system based on RFID location information, and can also be confirmed and adjusted manually in the system.

[0046] Usage and Measurement: Automatically records the equipment's cumulative running time, number of power on / off cycles, alarm history, and calibration records of key parameters.

[0047] Maintenance and Repair: Record the time, fault symptoms, repair content, replaced spare parts, repair cost, and repair personnel for each repair. Some of this information is supplemented by the predictive maintenance module after it automatically generates a work order, and some is entered into the system by the engineer after the repair is completed.

[0048] Metrology and Quality Control: Records the periodic metrological verification dates, result reports, and next verification dates for the equipment, and has an automatic reminder function for due dates.

[0049] Scrapping: Record the equipment scrapping application, approval process, scrapping date, and disposal method.

[0050] By leveraging a three-layer IoT architecture, combined with various sensors, positioning technologies, data analysis algorithms, and automated processes, comprehensive perception, intelligent analysis, proactive early warning, and closed-loop management of medical devices can be achieved, thereby effectively improving the management efficiency, safety, and lifecycle value of medical equipment.

[0051] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A medical device status management system based on Internet of Things (IoT) technology, characterized in that, include: A sensing layer, disposed on the body of the medical device, is used to collect multi-dimensional status data of the medical device; the sensing layer includes: The unique identification and positioning module is used to provide a unique identifier for medical devices and enable spatial positioning. The environmental sensing module is used to collect environmental parameters of the environment in which the medical device is located. The operation sensing module is used to collect the operating parameters of the medical device itself; The network layer, connected to the perception layer, includes a wireless communication module for building a wireless sensor network and receiving and transmitting multi-dimensional state data collected by the perception layer. The management layer, deployed on a cloud server and communicatively connected to the network layer, is used to receive and process the diverse state data; the management layer includes: The data processing module is used to clean and store the received multi-state data; The status analysis module is used to generate and display real-time status information of medical devices based on the processed data. The predictive maintenance module is used to predict potential failures of medical devices based on historical status data.

2. The medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The unique identification and positioning module includes an RFID tag or QR code module for unique identification of medical devices. The network layer or management layer dynamically tracks the medical device based on the received signal strength indication (RSSI) or time-of-flight (ToF) positioning algorithm, combined with the information from the unique identification and positioning module, to determine the room or bed location where the device is located.

3. The medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The network layer uses a dedicated IoT wireless platform that supports multi-device network management for data transmission; the platform is configured to maintain stable transmission quality in medical environments with wireless interference and to achieve data interface with hospital information systems (HIS) or mobile nursing systems (MCS).

4. A medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The management layer also includes a rule-based alarm system. The alarm system has preset parameter thresholds related to medical devices. When the detected device parameters exceed the preset thresholds, it automatically pushes alarm information to the associated mobile terminals and records alarm logs.

5. A medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The predictive maintenance module has a built-in trained machine learning algorithm model. The model is trained based on historical fault data and corresponding operating parameters to output prediction results of potential equipment faults and automatically generate maintenance work orders based on the prediction results.

6. A medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The environmental sensing module includes a temperature and humidity sensor and / or a vibration sensor for real-time monitoring of temperature and humidity parameters around the medical device. The status analysis module evaluates the impact of these environmental parameters on the device's performance based on these parameters.

7. A medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The management layer also includes a full lifecycle management module, which records and manages data for the entire process of medical devices from procurement, warehousing, allocation, use, maintenance to disposal, forming traceable and auditable electronic records.

8. A medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The operation sensing module includes a sound sensor and / or a current sensor; the status analysis module determines whether the medical device is in normal working condition by analyzing the device operation sound characteristics collected by the sound sensor or by analyzing the current waveform collected by the current sensor.

9. A medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The status analysis module provides a web-based visualization interface for graphically displaying the real-time operating status, geographical location information, and environmental parameters of medical devices, and supports searching by device type, department, or operating status.

10. A medical device status management system based on Internet of Things (IoT) technology according to claim 1, characterized in that, The wireless communication module includes a low-power wide-area network (LPWAN) module, a Wi-Fi module, or a 5G communication module, used to build a wireless sensor network including routers and coordinators to transmit data to the back-end server in real time.

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