A child blood disease isolation ward adaptive protection system based on physiological-environment closed loop feedback

Abstract

The application discloses a child blood disease isolation ward self-adaptive protection system based on physiological-environment closed-loop feedback and belongs to the technical field of medical environment control. The system comprises a physiological sensing layer, an environment sensing layer, an infection risk prediction engine, a laminar air curtain active isolation module, a physiological-environment closed-loop controller and an edge control unit. Through multi-modal environment sensing, feedforward control, edge computing and self-learning mechanism, the system realizes accurate and self-adaptive adjustment of ward temperature and humidity, cleanliness, air distribution and microbial concentration, guarantees the safety of sick children and improves environmental comfort and system reliability.

Description

Technical Field

[0001] This invention relates to the field of medical environment control technology, and more specifically to an adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback. Background Technology

[0002] Children with blood diseases (such as leukemia) need to be kept in a protective isolation environment for a long time during treatment because their immune function is extremely low, in order to prevent cross-infection.

[0003] Current ward environment control mostly uses constant parameter settings (such as constant temperature and constant fresh air volume), which cannot be dynamically adjusted according to the physiological state of the child, the activities of medical staff and changes in the external environment.

[0004] Meanwhile, traditional building automation systems lack microbial control, airflow organization optimization, and sensor fault tolerance mechanisms for isolation wards, resulting in problems such as control lag, large environmental disturbances, and high risk of equipment failure, making it difficult to meet the high standards required for isolation environments for pediatric hematological diseases.

[0005] Therefore, how to provide an adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, the present invention provides an adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback, in order to solve the technical problems existing in the prior art.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: An adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback includes: The physiological sensing layer is used to collect real-time data on the child's heart rate, respiratory rate, body surface temperature distribution, and activity status. The environmental sensing layer is used to collect ward environmental parameters and external disturbance signals; The infection risk prediction engine is communicatively connected to the physiological perception layer and the environmental perception layer. It is used to calculate the instantaneous infection risk index based on the collected data and dynamically adjust the system protection level according to the risk index. The laminar flow air curtain active isolation module is deployed at the ward entrance to dynamically adjust the air curtain flow rate and door pressure difference according to the door magnetic switch signal and protection level to form a dynamic physical isolation barrier. The physiological-environment closed-loop controller is communicatively connected to the physiological sensing layer and the environmental sensing layer. When the heart rate or respiratory rate of the child deviates from the baseline or the activity state is determined to be agitated, it automatically switches to the soothing mode and adjusts the lighting color temperature, illuminance and air supply speed to respond to the child's stress state. Edge control unit, used for multimodal sensor data verification and actuator fault protection.

[0008] Furthermore, the physiological sensing layer includes a non-contact millimeter-wave radar sensor and a thermal imaging sensor; The millimeter-wave radar sensor uses a frequency-modulated continuous wave system. It calculates heart rate and respiratory rate by extracting the phase changes of the micro-motion echo in the chest cavity, and identifies the child's activity status as quiet sleep, mild activity, or agitation based on the point cloud change rate.

[0009] Furthermore, the environmental sensing layer includes a temperature and humidity sensor, a microbial aerosol sensor, a PM2.5 sensor, an airflow sensor, and a door magnetic switch.

[0010] Furthermore, the instantaneous infection risk index defined by the infection risk prediction engine is: ; in, Real-time microbial concentration, This is a safety threshold; For personnel density, Maximum permissible personnel density; This represents the change in pressure difference at the doorway. Use the differential pressure disturbance threshold as a reference. This is a reference value for normal immune levels; For the child's immune status parameters, , , , These are dynamic weighting coefficients.

[0011] Furthermore, the laminar flow air curtain active isolation module includes a door magnetic switch signal detector, an adjustable air curtain nozzle, and a differential pressure controller; When the door magnetic switch signal detector detects an open signal, the differential pressure controller increases the air curtain flow rate from the base value to the enhanced value and continues for a set time. When the PM2.5 or microbial concentration in the external corridor exceeds the threshold, the differential pressure controller automatically increases the air curtain flow rate and differential pressure, regardless of whether the door is open or not.

[0012] Furthermore, the edge control unit includes a sensor redundancy fusion module and a device fault isolation module.

[0013] Furthermore, the sensor redundancy fusion module employs dual-modal cross-validation of heart rate and respiratory rate using millimeter-wave radar and thermal imaging pulsation signals. When any sensor data continuously deviates from the confidence interval, it automatically masks and enables the data fusion model prediction value.

[0014] Furthermore, it also includes a personalized thermal comfort control module, which dynamically adjusts the air conditioning setting temperature based on the deviation between the child's body surface temperature and the thermal neutral temperature, which is obtained through self-learning from historical data.

[0015] As can be seen from the above technical solution, compared with the prior art, the present invention provides an adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback. Through multimodal environmental perception, feedforward control, edge computing and self-learning mechanisms, it achieves precise and adaptive adjustment of ward temperature and humidity, cleanliness, airflow organization and microbial concentration, ensuring the safety of children and improving environmental comfort and system reliability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1 This is a structural schematic diagram provided for the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] See Figure 1 This invention discloses an adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback, comprising: The physiological sensing layer is used to collect real-time data on the child's heart rate, respiratory rate, body surface temperature distribution, and activity status. The environmental sensing layer is used to collect ward environmental parameters and external disturbance signals; The infection risk prediction engine is communicatively connected to the physiological perception layer and the environmental perception layer. It is used to calculate the instantaneous infection risk index based on the collected data and dynamically adjust the system protection level according to the risk index. The laminar flow air curtain active isolation module is deployed at the ward entrance to dynamically adjust the air curtain flow rate and door pressure difference according to the door magnetic switch signal and protection level to form a dynamic physical isolation barrier. The physiological-environment closed-loop controller is communicatively connected to the physiological sensing layer and the environmental sensing layer. When the heart rate or respiratory rate of the child deviates from the baseline or the activity state is determined to be agitated, it automatically switches to the soothing mode and adjusts the lighting color temperature, illuminance and air supply speed to respond to the child's stress state. Edge control unit, used for multimodal sensor data verification and actuator fault protection.

[0020] In one specific embodiment, the physiological sensing layer is deployed in a non-contact sensor array on the ceiling of the ward or beside the bed, including a non-contact millimeter-wave radar sensor and a thermal imaging sensor; The millimeter-wave radar sensor transmits frequency-modulated continuous waves, which are reflected by micro-motions in the chest cavity. The phase changes are then extracted to calculate heart rate (HR) and respiratory rate (RR). Signal processing is as follows: Suppose the difference frequency signal between the received and transmitted signals is used to separate the respiratory and heartbeat components through bandpass filtering. Then, through peak detection and interval estimation, the following is obtained: ; Thermal imaging sensor: Collects the surface temperature distribution of the child's body, extracts the core surface temperature through the facial area, and combines it with the ambient temperature to obtain the estimated core body temperature value.

[0021] It also includes: an activity status recognition module: based on the millimeter-wave radar point cloud change rate, it identifies whether the child is in a "quiet sleep", "mild activity" or "restless" state.

[0022] In one specific embodiment, the environmental sensing layer includes a temperature and humidity sensor, a microbial aerosol sensor, a PM2.5 sensor, an airflow sensor, and a door magnetic switch.

[0023] In one specific embodiment, the instantaneous infection risk index defined by the infection risk prediction engine is: ; in, Real-time microbial concentration, This is a safety threshold; For personnel density, Maximum permissible personnel density; This represents the change in pressure difference at the doorway. Use the differential pressure disturbance threshold as a reference. This is a reference value for normal immune levels; For the child's immune status parameters, , , , These are dynamic weighting coefficients.

[0024] In one specific implementation, the transient infection risk index is correlated with current clinical protective isolation grading: low-risk areas ( <0.4): Routine laminar flow operation, allowing necessary medical and nursing activities; Medium-risk areas (0.4≤ <0.7): Increase fresh air volume, pressurize the air curtain at the entrance, and restrict the number of people entering; High-risk areas ( ≥0.7): Activate the highest protection mode, suspend non-emergency medical procedures, and notify the infection control team for assessment.

[0025] This hierarchical mapping enables seamless integration of technical control and clinical management, improving the clinical acceptability of the system.

[0026] Traditional environmental monitoring systems only issue alarms when monitored parameters (such as microbial concentration) exceed the standard, at which point the risk of infection has already existed. The instantaneous infection risk index of this invention, by integrating immune status and dynamic disturbance factors, can predict an increased risk even before the microbial concentration reaches the threshold, when there is increased human activity or frequent disturbances at the entrance. It automatically activates enhanced protection, achieving proactive protection before the risk arrives, transforming post-event alarms into pre-event predictions.

[0027] This invention introduces immune status parameters for infected children, enabling the system to automatically identify children with severely suppressed immune systems and respond more sensitively to environmental fluctuations. This allows for precise stratified management, providing high protection for high-risk children and moderate protection for stable children. Simultaneously, this invention quantifies the degree of disturbance to the air curtain / pressure difference as a risk indicator. When doors are frequently opened or external contaminants intrude, the system can proactively enhance the air curtain flow rate, creating dynamic compensation and significantly improving the robustness of the isolation barrier.

[0028] Specifically, this invention is a systematic innovation based on the intersection of infection control, clinical hematology, fluid mechanics, and multi-sensor fusion control. It transforms the originally qualitative and empirical risk assessment of isolation wards into a calculable, controllable, and optimizable mathematical model, which is the intelligent central hub of the entire adaptive protection system and the core innovation that distinguishes it from traditional building automation and conventional environmental monitoring systems.

[0029] In one specific embodiment, the laminar air curtain active isolation module includes a door magnetic switch signal detector, an adjustable air curtain nozzle, and a differential pressure controller; When the door magnetic switch signal detector detects an open signal, the differential pressure controller increases the air curtain flow rate from the base value to the enhanced value and continues for a set time. When the PM2.5 or microbial concentration in the external corridor exceeds the threshold, the differential pressure controller automatically increases the air curtain flow rate and differential pressure, regardless of whether the door is open or not.

[0030] Specifically, the air curtain pressure differential setpoint is dynamically adjusted based on the infection risk index: .

[0031] In one specific embodiment, the edge control unit includes a sensor redundancy fusion module and a device fault isolation module.

[0032] In one specific embodiment, the sensor redundancy fusion module uses dual-modal cross-validation of heart rate and respiratory rate using millimeter-wave radar and thermal imaging pulsation signals. When any sensor data continuously deviates from the confidence interval, it automatically masks and enables the data fusion model prediction value.

[0033] In one specific embodiment, a personalized thermal comfort control module is also included, which dynamically adjusts the air conditioning set temperature based on the deviation between the child's body surface temperature and the thermal neutral temperature, which is obtained through self-learning from historical data.

[0034] Establish a thermal comfort deviation model based on the child's body surface temperature: ; T-type comfort preferences of patients are learned through historical data. neutral (Thermal neutral temperature), dynamically adjust the air conditioner setting temperature to maintain the body surface temperature within the individual's comfort range.

[0035] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0036] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback, characterized in that, include: The physiological sensing layer is used to collect real-time data on the child's heart rate, respiratory rate, body surface temperature distribution, and activity status. The environmental sensing layer is used to collect ward environmental parameters and external disturbance signals; The infection risk prediction engine is communicatively connected to the physiological perception layer and the environmental perception layer. It is used to calculate the instantaneous infection risk index based on the collected data and dynamically adjust the system protection level according to the risk index. The laminar flow air curtain active isolation module is deployed at the ward entrance to dynamically adjust the air curtain flow rate and door pressure difference according to the door magnetic switch signal and protection level to form a dynamic physical isolation barrier. The physiological-environment closed-loop controller is communicatively connected to the physiological sensing layer and the environmental sensing layer. When the heart rate or respiratory rate of the child deviates from the baseline or the activity state is determined to be agitated, it automatically switches to the soothing mode and adjusts the lighting color temperature, illuminance and air supply speed to respond to the child's stress state. Edge control unit, used for multimodal sensor data verification and actuator fault protection.

2. The adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback as described in claim 1, characterized in that, The physiological sensing layer includes a non-contact millimeter-wave radar sensor and a thermal imaging sensor. The millimeter-wave radar sensor uses a frequency-modulated continuous wave system. It calculates heart rate and respiratory rate by extracting the phase changes of the micro-motion echo in the chest cavity, and identifies the child's activity status as quiet sleep, mild activity, or agitation based on the point cloud change rate.

3. The adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback as described in claim 1, characterized in that, The environmental sensing layer includes a temperature and humidity sensor, a microbial aerosol sensor, a PM2.5 sensor, an airflow sensor, and a door magnetic switch.

4. The adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback as described in claim 1, characterized in that, The instantaneous infection risk index defined by the infection risk prediction engine is: ； in, Real-time microbial concentration, This is a safety threshold; For personnel density, Maximum permissible personnel density; This represents the change in pressure difference at the doorway. Use the reference differential pressure disturbance threshold; This is a reference value for normal immune levels; For the child's immune status parameters, , , , These are dynamic weighting coefficients.

5. The adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback as described in claim 1, characterized in that, The laminar air curtain active isolation module includes a door magnetic switch signal detector, an adjustable air curtain nozzle, and a differential pressure controller. When the door magnetic switch signal detector detects an open signal, the differential pressure controller increases the air curtain flow rate from the base value to the enhanced value and continues for a set time. When the PM2.5 or microbial concentration in the external corridor exceeds the threshold, the differential pressure controller automatically increases the air curtain flow rate and differential pressure, regardless of whether the door is open or not.

6. The adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback as described in claim 1, characterized in that, The edge control unit includes a sensor redundancy fusion module and a device fault isolation module.

7. The adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback as described in claim 6, characterized in that, The sensor redundancy fusion module uses dual-modal cross-validation of heart rate and respiratory rate using millimeter-wave radar and thermal imaging pulsation signals. When any sensor data continuously deviates from the confidence interval, it automatically masks and enables the data fusion model prediction value.

8. The adaptive protection system for pediatric hematological isolation wards based on physiological-environmental closed-loop feedback as described in claim 1, characterized in that, It also includes a personalized thermal comfort control module, which dynamically adjusts the air conditioning setting temperature based on the deviation between the child's body surface temperature and the thermal neutral temperature, which is obtained through self-learning from historical data.

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