Automated Respiration Detection from Neonatal Video Data

Ninah Koolen, Olivier Decroupet, Anneleen Dereymaeker, Katrien Jansen, Jan Vervisch, Vladimir Matic, Bart Vanrumste, Gunnar Naulaers, Sabine Van Huffel, Maarten De Vos

2015

Abstract

In the interest of the neonatal comfort, the need for noncontact respiration monitoring increases. Moreover, home respiration monitoring would be beneficial. Therefore, the goal is to extract the respiration rate from video data included in a polysomnography. The presented method first uses Eulerian video magnification to amplify the respiration movements. A respiration signal is obtained through the optical flow algorithm. Independent component analysis and principal component analysis are applied to improve the signal quality, with minor enhancement of the signal quality. The respiratory rate is extracted as the dominant frequency in the spectrograms obtained using the short-time Fourier transform. Respiratory rate detection is successful (94.12%) for most patients during quiet sleep stages. Real-time monitoring could possibly be achieved by lowering the spatial and temporal resolutions of the input video data. The outline for successful video-aided detection of the respiration pattern is shown, thereby paving the way for improvement of the overall assessment in the NICU and application in a home-friendly environment.

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Paper Citation


in Harvard Style

Koolen N., Decroupet O., Dereymaeker A., Jansen K., Vervisch J., Matic V., Vanrumste B., Naulaers G., Van Huffel S. and De Vos M. (2015). Automated Respiration Detection from Neonatal Video Data . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-758-077-2, pages 164-169. DOI: 10.5220/0005187901640169


in Bibtex Style

@conference{icpram15,
author={Ninah Koolen and Olivier Decroupet and Anneleen Dereymaeker and Katrien Jansen and Jan Vervisch and Vladimir Matic and Bart Vanrumste and Gunnar Naulaers and Sabine Van Huffel and Maarten De Vos},
title={Automated Respiration Detection from Neonatal Video Data},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2015},
pages={164-169},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005187901640169},
isbn={978-989-758-077-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - Automated Respiration Detection from Neonatal Video Data
SN - 978-989-758-077-2
AU - Koolen N.
AU - Decroupet O.
AU - Dereymaeker A.
AU - Jansen K.
AU - Vervisch J.
AU - Matic V.
AU - Vanrumste B.
AU - Naulaers G.
AU - Van Huffel S.
AU - De Vos M.
PY - 2015
SP - 164
EP - 169
DO - 10.5220/0005187901640169