Robust estimation and tracking of heart rate by PPG signal analysis

Photoplethysmography (PPG) is a widely used technology, routinely employed for heart rate measurement in low-cost medical devices. Monitoring is notoriously more difficult during physical exercise, since motion artifacts may considerably degrade PPG signals. The approach discussed in this paper estimates human heart rate and reliably tracks its charges by a robust algorithm, whose main steps include denoising by joint principal component analysis, Fourier-based heart rate measurement and, finally, smoothing and tracking by a Kalman filter. To illustrate overall performance, experimental results are presented using publicly available real-life PPG traces