Review on Heart-Rate Estimation from Photoplethysmography and Accelerometer Signals During Physical Exercise
Non-invasive monitoring of physiological signals during physical exercise is essential to customize the exercise module. Photoplethysmography (PPG) signal has often been used to non-invasively monitor heart-rate, respiratory rate, and blood-pressure among other physiological signals. Typically, PPG...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/85626 http://hdl.handle.net/10220/43914 |
| Summary: | Non-invasive monitoring of physiological signals during physical exercise is essential to customize the exercise module. Photoplethysmography (PPG) signal has often been used to non-invasively monitor heart-rate, respiratory rate, and blood-pressure among other physiological signals. Typically, PPG signal is acquired using pulse oximeter from finger-tip or wrist. Advantage of wrist-based PPG sensors is that it is more convenient to wear. Other sensors such as accelerometer can also be integrated with it due to large area on the wrist. This article provides a review of the algorithms developed for heart rate estimation during physical exercise from the PPG signals and accelerometer signals. The datasets used to develop these techniques are described. Algorithms for denoising of PPG signals using accelerometer signals are either in time domain or frequency domain. |
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