Key result
The AFODSS dual-optimization technique achieved an average absolute error of 1.35 beats/min for heart rate estimation from PPG signals during intense exercise.
Why the study?
Direct heart rate estimation from PPG sensors during physical exercise often yields erroneous output due to high motion artifacts.
Does the AFODSS algorithm improve heart rate estimation accuracy from PPG signals with motion artifacts in subjects during intense exercise?
Does the AFODSS algorithm improve heart rate estimation accuracy from PPG signals with motion artifacts in subjects during intense exercise?
The AFODSS algorithm provides highly accurate heart rate estimation from PPG signals during intense exercise by effectively neutralizing motion artifacts.
Enhances PPG heart rate estimation during intense activity; leaves open validation in diverse clinical settings.
Precise heart rate (HR) estimation of individuals during physical exercise from PPG sensors using direct methods often produces erroneous output due to the occurrence of exceedingly high motion artifacts (MAs). The effect of MAs can be neutralized using non-direct algorithms such as optimization techniques using some a priori about MA. In this paper, we propose a dual-optimization technique using adaptive Fourier decomposition in conjunction with sparse spectral reconstruction (AFODSS) using a multiple measurement vectors (MMVs) model and a regularized bi-conjugate gradient focal underdetermined system solver (BCG-FOCUSS) algorithm. Using AFODSS, the average absolute error (AAE) of HR obtained on the dataset recorded from 23 subjects during their intense exercise is 1.35 beats/min. The BCG-FOCUSS algorithm used in this paper helps to speed up the convergence rate and reduce time complexity when compared with other FOCUSS algorithms.
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Raj et al. (2019) studied Heart rate estimation during physical exercise (n=23). AFODSS (adaptive Fourier decomposition with sparse spectral reconstruction) was evaluated on Average absolute error (AAE) of heart rate. The AFODSS dual-optimization technique achieved an average absolute error of 1.35 beats/min for heart rate estimation from PPG signals during intense exercise.
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