A wavelet-based denoising approach significantly reduced heart rate and heart rate variability estimation errors caused by vertical and circular motion artifacts.
Does a wavelet-based denoising method reduce HR and HRV estimation errors caused by motion artifacts in photoplethysmographic recordings?
A wavelet-based denoising approach significantly reduces heart rate and heart rate variability estimation errors caused by motion artifacts in photoplethysmography.
In this work, the effects of motion artifacts on photoplethysmographic signals obtained at fingertip was evaluated. A wavelet-based method was proposed to reduce the influence of motion artifacts on heart rate (HR) and heart rate variability (HRV) estimation. Two kinds of motions were investigated - vertical and circular motions. During the motion, reference signals were acquired at other hand as a standard. Results show that the HR and HRV estimation error can be reduced significantly.
Lee et al. (2004) studied Motion artifacts in photoplethysmographic signals. Wavelet denoising approach vs. Reference signals acquired at other hand was evaluated on Heart rate (HR) and heart rate variability (HRV) estimation error. A wavelet-based denoising approach significantly reduced heart rate and heart rate variability estimation errors caused by vertical and circular motion artifacts.