Abstract

Monitoring of respiration and body movements during sleep is a part of screening sleep disorders related to health status. Nowadays, thermal-based methods are presented to monitor the sleeping person without any sensors attached to the body to protect privacy. A non-contact respiration monitoring based on thermal videos requires visible facial landmarks like nostril and mouth. The limitation of these techniques is the failure of face detection while sleeping with a fixed camera position. This study presents the non-contact respiration monitoring approach that does not require facial landmark visibility under the natural sleep environment, which implies an uncontrolled sleep posture, darkness, and subjects covered with a blanket. The automatic region of interest (ROI) extraction by temperature detection and breathing motion detection is based on image processing integrated to obtain the respiration signals. A signal processing technique was used to estimate respiration and body movements information from a sequence of thermal video. The proposed approach has been tested on 16 volunteers, for which video recordings were carried out by themselves. The participants were also asked to wear the Go Direct respiratory belt for capturing reference data. The result revealed that our proposed measuring respiratory rate obtains root mean square error (RMSE) of bpm. The advantage of this approach lies in its simplicity and accessibility to serve users who require monitoring the respiration during sleep without direct contact by themselves.

Highlights

  • The respiratory rate is one of the critical vital signs that indicate health problems

  • The present study aims to develop the measuring system capable of non-contact monitoring of respiration and body movements in natural sleep environments using a thermal video

  • The experiments were conducted on real-life conditions, and volunteers were invited to record in their room while they were sleeping. They placed a respiratory belt around their ribs and mounted a thermal camera on a tripod by themselves before they go to bed

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Summary

Introduction

The respiratory rate is one of the critical vital signs that indicate health problems. Several approaches have been proposed to monitor respiration with a thermal camera by detecting the temperature change around the nostrils [18,21,22,23,24,25,26,27,28] or the airflow [19,20,29] in seated positions They set the nose or the mouth as the region of interest (ROI) that can be defined manually or automatically by using anatomical features integrated with tracking algorithms [18,21,22,23,25]. Usman et al [30] adopted thermal imaging to detect sleep apnea and study in a variety of breathing patterns They used the Kanade–Lucas–Tomasi tracking algorithm to track the manual selected nose region.

Proposed Method
Respiration Monitoring
Automatic ROI Detection
Breathing Motion Detection
Respiration Signal Analysis
Body Movements Detection
Experimental Results
Experimental Setup
Respiratory Rate Estimation and Body Movements Detection
Conclusions
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