Research Article
Detecting Bed Occupancy Using Thermal Sensing Technology: A Feasibility Study
@INPROCEEDINGS{10.1007/978-3-030-99194-4_6, author={Rebecca Hand and Ian Cleland and Chris Nugent and Jonathan Synnott}, title={Detecting Bed Occupancy Using Thermal Sensing Technology: A Feasibility Study}, proceedings={Pervasive Computing Technologies for Healthcare. 15th EAI International Conference, Pervasive Health 2021, Virtual Event, December 6-8, 2021, Proceedings}, proceedings_a={PERVASIVEHEALTH}, year={2022}, month={3}, keywords={Thermal sensor Bed occupancy detection Bed pressure sensor Contactless sleep monitoring Background subtraction Residual heat}, doi={10.1007/978-3-030-99194-4_6} }- Rebecca Hand
Ian Cleland
Chris Nugent
Jonathan Synnott
Year: 2022
Detecting Bed Occupancy Using Thermal Sensing Technology: A Feasibility Study
PERVASIVEHEALTH
Springer
DOI: 10.1007/978-3-030-99194-4_6
Abstract
Measures of sleep and its disturbances can be detected by monitoring bed occupancy. These measures can also be used for alerting of bed exits or for determining sleep quality. This paper introduces an unobtrusive approach to detecting bed occupancy using low resolution thermal sensing technology. Thermal sensors operate regardless of lighting conditions and offer a high level of privacy making them ideal for the bedroom environment. The optimum bed occupancy detection algorithm was determined and tested on over 55,000 frames of 32 × 32 thermal sensor data. The developed solution to detect bed occupancy achieved an accuracy of 0.997. In this approach the location of the bed and the location of the participant is considered by classification rules to determine bed occupancy. The approach was evaluated using thermal sensor and bed pressure sensor data. Future work will focus on automatic detection of the bed location and improving the system by further reducing the false positives caused from residual heat.
