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Sensors 2017, 17(2), 286; doi:10.3390/s17020286

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

1
School of Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia
2
Electrical Engineering Technical College, Middle Technical University, Al Doura 10022, Baghdad, Iraq
3
School of Nursing and Midwifery, University of South Australia, Adelaide, SA 5001, Australia
4
Joint and Operations Analysis Division, Defence Science and Technology Group, Melbourne, Victoria 3207, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Changzhi Li
Received: 18 November 2016 / Revised: 27 January 2017 / Accepted: 30 January 2017 / Published: 3 February 2017
(This article belongs to the Special Issue Non-Contact Sensing)
View Full-Text   |   Download PDF [6335 KB, uploaded 3 February 2017]   |  

Abstract

The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications. View Full-Text
Keywords: apnoea; apparent life-threatening event; Microsoft Kinect sensor; real-time image sequence analysis; motion magnification; motion detection apnoea; apparent life-threatening event; Microsoft Kinect sensor; real-time image sequence analysis; motion magnification; motion detection
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MDPI and ACS Style

Al-Naji, A.; Gibson, K.; Lee, S.-H.; Chahl, J. Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study. Sensors 2017, 17, 286.

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