Monitoring Sleep Posture Based on Temperature and Humidity Sensor

In this paper, we proposed a method of attaching seven temperature and humidity sensors to a pillow and monitoring changes in temperature and humidity to determine sleeping posture. The existing method of determining sleep position is to monitor changes in pressure using FSR sensors mounted inside a...

Full description

Saved in:
Bibliographic Details
Published inInternational Conference on Artificial Intelligence in Information and Communication (ICAIIC) (Online) pp. 022 - 025
Main Authors Kim, Hyung-Ju, Jun, Won-Ho, Shin, Woo-Chul, Hong, Youn-Sik
Format Conference Proceeding
LanguageEnglish
Published IEEE 19.02.2024
Subjects
CNN
data labeling
Humidity
Humidity measurement
Machine learning
Sleep
sleep posture
temperature and humidity sensor
Temperature distribution
Temperature measurement
Temperature sensors
Online AccessGet full text

Cover

More Information
Summary:In this paper, we proposed a method of attaching seven temperature and humidity sensors to a pillow and monitoring changes in temperature and humidity to determine sleeping posture. The existing method of determining sleep position is to monitor changes in pressure using FSR sensors mounted inside a pillow. Changes in pressure are limited to simply identifying changes in head movement, but changes in temperature and humidity have the advantage of being able to identify physical changes in the subject. For machine learning modeling, the temperature and humidity dataset accumulated during sleep was subjected to a data labeling process through discrimination of sleep posture images. With the CNN-based modeling the accuracy of discriminating sleep posture reached about 95%. This confirms that temperature and humidity sensor-based sleeping posture monitoring is sufficiently applicable.
ISSN:2831-6983
DOI:10.1109/ICAIIC60209.2024.10463422