TY - GEN
T1 - Improvement of Environment and Camera Setting on Extraction of Heart Rate Using Eulerian Video Magnification
AU - Huang, Bo Yu
AU - Lin, Chi Lun
N1 - Funding Information:
Acknowledgment. This research was supported by the Ministry of Science and Technology, Taiwan, R.O.C. under Grants No. MOST 106-2221-E-006-049 and No. MOST 107-2221-E-006-067-MY2. The authors would like to thank our colleagues from Medical Device Innovation and Design Laboratory in the Department of Mechanical Engineering, National Cheng Kung University who provided their insights and expertise that greatly assisted the research.
Funding Information:
This research was supported by the Ministry of Science and Technology, Taiwan, R.O.C. under Grants No. MOST 106-2221-E-006-049 and No. MOST 107-2221-E-006-067-MY2. The authors would like to thank our colleagues from Medical Device Innovation and Design Laboratory in the Department of Mechanical Engineering, National Cheng Kung University who provided their insights and expertise that greatly assisted the research.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Non-contact heart rate measurement has been widely utilized in multiple applications. The Eulerian Video Magnification algorithm proposed by MIT CSAIL group in 2012 can be used to magnify the subtle color variation and small motion in videos and can be used to extract cardio-features through photoplethysmography method. In this study, we intend to improve the accuracy of heart rate prediction for the Eulerian Video Magnification method. With the selected region of interest and the peak detection algorithm, we found out that the signal of the Y component in YIQ color spectrum is more consistent than that of the I component in terms of heart rate estimation. The result also demonstrated that the heart rate extracted under 30 frames per second (fps) was more accurate than which extracted under 60 fps. With an illumination level higher than 1500 lx and a frame rate of 30 fps, the error of heart rate extraction compared to oximeter measurement was 5% while using GoPro Hero 6 for recording. Further data processing and false peak detection are necessary for accurate heart rate variability characterization.
AB - Non-contact heart rate measurement has been widely utilized in multiple applications. The Eulerian Video Magnification algorithm proposed by MIT CSAIL group in 2012 can be used to magnify the subtle color variation and small motion in videos and can be used to extract cardio-features through photoplethysmography method. In this study, we intend to improve the accuracy of heart rate prediction for the Eulerian Video Magnification method. With the selected region of interest and the peak detection algorithm, we found out that the signal of the Y component in YIQ color spectrum is more consistent than that of the I component in terms of heart rate estimation. The result also demonstrated that the heart rate extracted under 30 frames per second (fps) was more accurate than which extracted under 60 fps. With an illumination level higher than 1500 lx and a frame rate of 30 fps, the error of heart rate extraction compared to oximeter measurement was 5% while using GoPro Hero 6 for recording. Further data processing and false peak detection are necessary for accurate heart rate variability characterization.
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U2 - 10.1007/978-3-030-30636-6_52
DO - 10.1007/978-3-030-30636-6_52
M3 - Conference contribution
AN - SCOPUS:85075806042
SN - 9783030306359
T3 - IFMBE Proceedings
SP - 381
EP - 388
BT - Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019
A2 - Lin, Kang-Ping
A2 - Magjarevic, Ratko
A2 - de Carvalho, Paulo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 4th International Conference on Biomedical and Health Informatics, ICBHI 2019
Y2 - 17 April 2019 through 20 April 2019
ER -