PARHELIA: Particle Filter-Based Heart Rate Estimation From Photoplethysmographic Signals During Physical Exercise

• Published in: IEEE transactions on biomedical engineering Vol. 65; no. 1; pp. 189 - 198
• Main Authors: Fujita, Yuya, Hiromoto, Masayuki, Sato, Takashi
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Accelerometers; Adolescent; Adult; Estimation; Exercise - physiology; Heart rate; Heart Rate - physiology; Heart rate estimation; Humans; Monitoring; motion artifact removal; particle filter; Photoplethysmography - methods; photoplethysmography (PPG); Physical exercise; Pollution measurement; Probability density function; Signal Processing, Computer-Assisted; Wrist; Young Adult
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2017.2697911

The photoplethysmographic (PPG) signal is an important source of information for estimating heart rate (HR). However, the PPG signal could be strongly contaminated by the motion artifact of the subjects, making HR estimation a particularly difficult problem. In this paper, we propose PARHELIA, a PARticle filter-based algorithm for HEart rate estimation using photopLethysmographIc signAls. The proposed method employs a particle filter, and utilizes the simultaneously recorded acceleration signals from a wrist-type sensor, to keep track of multiple HR candidates. This achieves quick recovery from incorrect HR estimations under the strong influence of the MA. Experimental results for a dataset of 12 subjects recorded during fast running showed that the average absolute estimation error was 1.17 beats per minute (BPM) whereas that of the best-known conventional method, JOSS, is 1.28 BPM. Furthermore, the estimation time of PARHELIA is 20 times shorter than JOSS.