Hospital Bed Sensor Control for Adaptive Gain and Noise Filtering
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Solution Overview
Problem
Current person support apparatuses, such as hospital beds, lack advanced sensor systems that can dynamically adjust sensor gain and filtering based on user position and movement, leading to suboptimal monitoring and therapy delivery.
Innovation Solution
A person support apparatus with a controller that adjusts sensor gain and filtering settings based on user position, movement, and sensor signal strength and clarity, incorporating multiple sensors and filtering options like high pass, low pass, and band pass filters, and the ability to selectively activate or deactivate sensors based on user position and therapy status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor gain is increased to improve signal detection, then measurement precision improves, but noise from medical equipment increases
Solution Approach 1:
The patent implements dynamic sensor control where the controller adjusts sensor gain and filtering parameters in real-time based on detected user position and movement. The system transitions from static sensor configuration to dynamic adaptation, optimizing signal detection while minimizing noise interference from medical equipment based on current operational conditions.
Solution Approach 2:
The system changes sensor operating parameters (gain levels and filter characteristics) based on detected conditions. The controller modifies gain and filtering parameters dynamically, allowing the sensor to adapt its sensitivity and frequency response to optimize measurement precision while reducing noise from medical equipment in different operational states.
2Loss of information
If multiple sensors are activated continuously to monitor all conditions, then measurement completeness improves, but energy consumption increases
Solution Approach 1:
The system activates only the necessary subset of sensors based on current user position and movement detection, rather than continuously running all sensors. The controller selectively enables sensors only when and where needed, reducing overall energy consumption while maintaining adequate monitoring coverage through targeted sensor activation.
Solution Approach 2:
The sensor activation scheme transitions from static continuous operation to dynamic selective activation. The controller continuously monitors user position and movement, dynamically adjusting which sensors remain active based on current operational requirements, thereby optimizing the balance between monitoring coverage and energy consumption.
3Speed
If sensor sampling rate is increased to capture rapid changes, then response speed improves, but noise from medical equipment increases
Solution Approach 1:
The system dynamically adjusts the sampling rate parameter based on user position and movement detection. When rapid changes are detected, the sampling rate increases to capture the event with high temporal resolution. When conditions are stable, the sampling rate decreases, reducing the amount of noise data collected from medical equipment while maintaining adequate monitoring capability.
Solution Approach 2:
The sampling rate transitions from a fixed parameter to a dynamic one that adapts to current operational conditions. The controller modifies sampling frequency in real-time based on detected user activity, optimizing the balance between response speed and noise reduction by adjusting data acquisition intensity according to actual monitoring needs.
4Measurement precision
If filtering is increased to reduce noise, then signal clarity improves, but response time increases
Solution Approach 1:
The system dynamically adjusts filter characteristics (cutoff frequencies, filter orders) based on user position and movement detection. When rapid changes are detected, the system uses lighter filtering to minimize processing delay and preserve response time. When conditions are stable, stronger filtering is applied to enhance signal clarity, thereby optimizing the trade-off between precision and response time adaptively.
Solution Approach 2:
The filtering parameters transition from static to dynamic, allowing the system to adapt filter strength based on current operational conditions. The controller adjusts filtering in real-time, applying stronger filters when signal clarity is prioritized and weaker filters when rapid response is needed, thus dynamically optimizing the balance between measurement precision and response time.
Data Source
AI summary
A person support apparatus includes a frame and a support surface cooperating with the frame to support a person. The person support apparatus also has a sensor coupled to one of the frame and the support surface. The sensor detects at least one characteristic associated with the person. A controller is coupled to the sensor. In response to at least one of a condition of the frame, a condition of the support surface, a position of the person, or a condition of the person, the controller operates to control the sensor by at least one of changing a gain of the sensor and changing a manner in which a signal from the sensor is filtered. In some instances, the controller turns the sensor off.