Key result
Novel dynamic time warping framework estimates HR from motion-corrupted ECGs with 2.5 BPM mean error.
Why the study?
Long-term wearable instantaneous heart rate monitoring is hindered by motion artifacts corrupting ECG signals, limiting pervasive heart health management.
Population
ECG signals from a wrist-ECG dataset acquired by a semicustomized platform and a public ECG dataset
Comparison
Phase-domain multiview dynamic time warping framework vs corrupted ECG signals without this method
Design
Other study design applying a novel signal processing framework
Authors
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May enable heart rate estimation amid intense motion; leaves open clinical validation before practice adoption.
The proposed phase-domain multiview dynamic time warping framework effectively estimates instantaneous heart rate from ECG signals corrupted by intense motion artifacts.
Zhang et al. (2016) studied ECG signals corrupted by motion artifacts. Phase-Domain Multiview Dynamic Time Warping framework vs. previously reported approaches was evaluated on Mean absolute error and root mean square error of the estimated instantaneous heart rate. A novel phase-domain multiview dynamic time warping framework estimated instantaneous heart rate from motion-corrupted ECG signals with a mean absolute error of 2.5 BPM.
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