Remote respiratory monitoring system based on developing motion magnification technique. (August 2016)

• Record Type: Journal Article
• Authors: Al-Naji, Ali; Chahl, Javaan
• Is Part Of: Biomedical signal processing and control. Volume 29(2016)
• Page Start: 1
• Page End: 10
• Publication Date: 2016-08
• Subjects: Video processing -- Motion magnification -- Wavelet pyramid decomposition -- Motion detection -- Frame subtraction; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2016.05.002
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: A non-contact method to measure respiratory activity parameters is presented. The method is suitable for measuring respiratory activity parameters for a sleeping baby at different poses, even in the presence of the blanket on the baby or unclear ROI. Video magnification techniques are used to magnify motion resulting from movement of the chest caused by inhalation and exhalation. Eulerian video magnification technique is developed by using a wavelet pyramid decomposition an elliptic band pass filter. The results with both magnification techniques have been compared. Abstract: The aim of this study is to detect and measure the rate and timing parameters of the respiratory cycle at a distance from different sleeping positions of a baby based on video imagery. This study relied on amplifying motion resulting from movement of the chest caused by inhalation and exhalation. A motion magnification technique based on a wavelet decomposition and an elliptic filter was used to magnify breathing movement that is difficult to see with the naked eye. A novel measuring method based on motion detection was used to measure respiratory rate and its time parameters by detecting the fastest moving areas in the magnified video frame sequences. The video frames were converted into a corresponding logical matrix. The experimental results on several videos for the baby at different sleeping positions show that the remote respiratory monitoring system has an accuracy of 99%. The proposed system has very low computational complexity, is feasible and safe making it suitable for the design of next generation non-contact vital signs monitoring systems.