S-Space College of Medicine/School of Medicine (의과대학/대학원) Biomedical Engineering (의공학전공) Journal Papers (저널논문_의공학전공)
Improved elimination of motion artifacts from a photoplethysmographic signal using a Kalman smoother with simultaneous accelerometry
Cited 108 time in Web of Science Cited 123 time in Scopus
- Issue Date
- IOP PUBLISHING LTD
- PHYSIOLOGICAL MEASUREMENT; Vol.31 12; 1585-1603
- photoplethysmography ; NLMS ; RLS ; Kalman filter ; motion artifact ; fixed-interval Kalman smoother
- A photoplethysmography (PPG) signal provides very useful information about a subject`s hemodynamic status in a hospital or ubiquitous environment. However, PPG is very vulnerable to motion artifacts, which can significantly distort the information belonging to the PPG signal itself. Thus, the reduction of the effects of motion artifacts is an important issue when monitoring the cardiovascular system by PPG. There have been many adaptive techniques to reduce motion artifacts from PPG signals. In the present study, we compared a method based on the fixed-interval Kalman smoother with the usual adaptive filtering algorithms, e. g. the normalized least mean squares, recursive least squares and the conventional Kalman filter. We found that the fixed-interval Kalman smoother reduced motion artifacts from the PPG signal most effectively. Therefore, the use of the fixed-interval Kalman smoother can reduce motion artifacts in PPG, thus providing the most reliable information that can be deduced from the reconstructed PPG signals.
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