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

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 PAR...

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Published inIEEE transactions on biomedical engineering Vol. 65; no. 1; pp. 189 - 198
Main Authors Fujita, Yuya, Hiromoto, Masayuki, Sato, Takashi
Format Journal Article
LanguageEnglish
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
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Abstract 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.
AbstractList 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.
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.
Author Hiromoto, Masayuki
Fujita, Yuya
Sato, Takashi
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  surname: Fujita
  fullname: Fujita, Yuya
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  fullname: Hiromoto, Masayuki
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  fullname: Sato, Takashi
  organization: Department of Communications and Computer Engineering, School of InformaticsKyoto University
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Snippet The photoplethysmographic (PPG) signal is an important source of information for estimating heart rate (HR). However, the PPG signal could be strongly...
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SubjectTerms 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
Title PARHELIA: Particle Filter-Based Heart Rate Estimation From Photoplethysmographic Signals During Physical Exercise
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