The authors collected and released over 350 hours of multi-site PPG, acceleration, and temperature data from four body-worn devices during free-living activities, with benchmarks showing site-dependent heart-rate estimation errors ranging from 2.3 bpm (earring) to 8.7 bpm (necklace).
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Nonlinear dimensionality reduction on ECG signals enables unsupervised personalized arrhythmia detection with high accuracy on 2D embeddings using standard algorithms on the MIT-BIH database.
rPPG algorithms with Lp-norm and fractional-order peak enhancement achieve 1.92 bpm MAE for pulse rate and good HRV metrics vs ECG in 29 drivers, recommending 2SR for rate and CHROM for variability with 20 superpixels.
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Multi-site PPG: An In-the-Wild Physiological Dataset from Emerging Multi-site Wearables
The authors collected and released over 350 hours of multi-site PPG, acceleration, and temperature data from four body-worn devices during free-living activities, with benchmarks showing site-dependent heart-rate estimation errors ranging from 2.3 bpm (earring) to 8.7 bpm (necklace).
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Manifold Learning for Personalized and Label-Free Detection of Cardiac Arrhythmias
Nonlinear dimensionality reduction on ECG signals enables unsupervised personalized arrhythmia detection with high accuracy on 2D embeddings using standard algorithms on the MIT-BIH database.
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A Signal Extraction Approach for Remote Heart Rate Variability Assessment Using Proxy Measure in a Driving Simulator
rPPG algorithms with Lp-norm and fractional-order peak enhancement achieve 1.92 bpm MAE for pulse rate and good HRV metrics vs ECG in 29 drivers, recommending 2SR for rate and CHROM for variability with 20 superpixels.