Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/I2MTC.2017.7969715 | 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) |
Keywords | Field | DocType |
robust heart rate estimation,robust heart rate tracking,PPG signal analysis,photoplethysmography,heart rate measurement,low-cost medical devices,physical exercise monitoring,motion artifacts,denoising,joint principal component analysis,Fourier-based heart rate measurement,Kalman filter smoothing,Kalman filter tracking,publicly available real-life PPG traces | Noise reduction,Signal processing,Accelerometer,Photoplethysmogram,Electronic engineering,Kalman filter,Fourier transform,Smoothing,Principal component analysis,Mathematics | Conference |
ISBN | Citations | PageRank |
978-1-5090-3597-7 | 1 | 0.38 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandra Galli | 1 | 4 | 1.58 |
| guglielmo frigo | 2 | 55 | 10.64 |
| Claudio Narduzzi | 3 | 138 | 20.65 |
| Giada Giorgi | 4 | 71 | 13.30 |