Bed Occupancy Detection Using Trailing Average Pressure Filtering
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Solution Overview
Problem
Existing bed systems lack accurate methods to determine user occupancy and biological activity, leading to inefficiencies in triggering events or displaying user data, as simple pressure threshold comparisons are noisy and influenced by external factors.
Innovation Solution
A bed system with a pressure sensor and controller that calculates a trailing average of pump pressure readings, identifying user presence by comparing instant readings to the average and adjusting thresholds for seasonality and user growth, while also considering biological activity indicators like heart rate and breathing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple pressure threshold comparison is used to detect user presence, then the system is simple to implement, but the measurement precision deteriorates due to noise and external factors
Solution Approach 1:
The system performs preliminary actions by calculating a trailing average of pressure readings before making the final occupancy determination. This preprocessing step filters out noise and external factors, allowing the system to maintain simplicity while improving measurement precision through statistical smoothing of the pressure data.
Solution Approach 2:
The trailing average pressure reading acts as an intermediary between the raw pressure sensor data and the final occupancy decision. By comparing the instant pressure reading against this intermediate averaged value rather than a fixed threshold, the system achieves more accurate occupancy detection while keeping the overall system architecture simple.
2Measurement precision
If trailing average calculation is implemented to filter noise, then measurement precision improves, but device complexity increases due to additional processing
Solution Approach 1:
The trailing average calculation is performed as a preliminary processing step that maintains a running average in memory rather than requiring complex real-time filtering algorithms. This approach improves measurement precision by smoothing noise while keeping the processing complexity low through efficient use of stored historical data.
Solution Approach 2:
The system uses its own historical pressure reading data to generate the trailing average, making the filtering process self-service rather than requiring external complex filtering systems. The controller itself maintains and updates the trailing average using simple arithmetic operations on stored values, improving precision without adding external complexity.
3Ease of operation
If fixed pressure threshold is used for occupancy detection, then the system is easy to operate, but adaptability deteriorates due to seasonality and user growth
Solution Approach 1:
The system transitions from a static fixed threshold to a dynamic adaptive threshold that automatically adjusts based on historical data, seasonality, and user growth patterns. The controller modifies the threshold value over time while maintaining ease of operation through automated adaptation, eliminating the need for manual recalibration and improving long-term detectability accuracy.
Solution Approach 2:
The system implements feedback by continuously monitoring pressure readings and using this information to automatically adjust the occupancy threshold. Historical occupancy data and environmental factors are fed back into the threshold calculation, allowing the system to adapt to seasonality and user growth while maintaining simple operation through automated self-adjustment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately determines user occupancy and biological activity, enabling precise control of peripheral devices and user interface updates, improving the accuracy of occupancy status and providing reliable user data.
Implementation Method 1
A bed system with a pressure sensor and controller that calculates a trailing average of pump pressure readings
Data Source
AI summary
If a user enters a bed, a sensor in the pump of the bed can detect the user's presence in the bed.