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Analysis of Sleep Breathing Type According to Breathing Strength  

Kang, Yunju (Dept. of Electronics and Information System Engineering, Sangmyung University)
Jung, Sungoh (Dept. of Electronics and Information System Engineering, Sangmyung University)
Kook, Joongjin (Dept. of Electronics and Information System Engineering, Sangmyung University)
Publication Information
Journal of the Semiconductor & Display Technology / v.20, no.3, 2021 , pp. 1-5 More about this Journal
Abstract
Sleep apnea refers to a condition in which a person does not breathe during sleep, and is a dangerous symptom that blocks oxygen supply in the body, causing various complications, and the elderly and infants can die if severe. In this paper, we present an algorithm that classifies sleep breathing by analyzing the intensity of breathing with images alone in preparation for the risk of sleep apnea. Only the chest of the person being measured is set to the Region of Interest (ROI) to determine the breathing strength by the differential image within the corresponding ROI area. The adult was selected as the target of the measurement and the breathing strength was measured accurately, and the difference in breathing intensity was also distinguished using depth information. Two videos of sleeping babies also show that even microscopic breathing motions smaller than adults can be detected, which is also expected to help prevent infant death syndrome (SIDS).
Keywords
Breathing Detection; Head Tracking; Motion Acquisition; Tiny-Motion; Sleep Monitoring; Video Image Processing;
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