標題: Motion Resistant Image-Photoplethysmography Based on Spectral Peak Tracking Algorithm
作者: Wu, Bing-Fei
Huang, Po-Wei
Lin, Chun-Hsien
Chung, Meng-Liang
Tsou, Tsong-Yang
Wu, Yu-Liang
電機工程學系
電控工程研究所
Department of Electrical and Computer Engineering
Institute of Electrical and Control Engineering
關鍵字: Biomedical signal processing;biomedical monitoring;heart rate;image sequence analysis;photoplethysmography (PPG);spectral peak tracking
公開日期: 1-一月-2018
摘要: Medical fields have seen increasing attention being given to image based heart rate measurement in recent years. One of the major limitations is motion artifacts of subject's head. Although there have been many studies focusing on signal extraction using different parameters and models, the development of frequency domain analysis is emerging slowly and moving in many directions. In the field of contact photoplethysmography (PPG), recent studies employed the acceleration signals to assist their spectral peak tracking algorithms. Inspired by the development of contact PPG, we are proposing a motion resistant spectral peak tracking (MRSPT) framework which eliminates the motion artifacts by integrating facial motion signals. The effectiveness of MRSPT coupled with the optimal image-based PPG (iPPG) signal has been tested against the state-of-the-art spectral peak tracking algorithms, multi-channel spectral matrix decomposition (MC-SMD), and the maximum peak selection coupled with optimal iPPG signal (Optimal MPS). Compared with MC-SMD and Optimal MPS, MRSPT uplifts the success rate-10 (success rate-5), the probability in which the absolute error is below ten (five) beats per mins, from 54.7% (36.3%) with MC-SMD and 73.0% (61.3%) with Optimal MPS to 90.7% (75.7%) with MRSPT in motion scenarios where subject moves arbitrarily with different distance or lighting. MRSPT also enhances the success rate-10 (success rate-5) from 40.7% (26.3%) with MC-SMD and 57.4% (45.7%) with Optimal MPS to 73.4% (58.4%) with MRSPT in all seven motion conditions including driving and running. Averagely, the success rate-five of Optimal MRSPT surpass the success rate-10 of both Optimal MPS and MC-SMD.
URI: http://dx.doi.org/10.1109/ACCESS.2018.2828133
http://hdl.handle.net/11536/144977
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2018.2828133
期刊: IEEE ACCESS
Volume: 6
起始頁: 21621
結束頁: 21634
顯示於類別:期刊論文