Unobtrusive heart rate estimation during physical exercise using photoplethysmographic and acceleration data

Photoplethysmography (PPG) is a non-invasive, inexpensive and unobtrusive method to achieve heart rate monitoring during physical exercises. Motion artifacts during exercise challenge the heart rate estimation from wrist-type PPG signals. This paper presents a methodology to overcome these limitation by incorporating acceleration information. The proposed algorithm consisted of four stages: (1) A wavelet based denoising, (2) an acceleration based denoising, (3) a frequency based approach to estimate the heart rate followed by (4) a postprocessing step. Experiments with different movement types such as running and rehabilitation exercises were used for algorithm design and development. Evaluation of our heart rate estimation showed that a mean absolute error 1∶96 bpm (beats per minute) with standard deviation of 2∶86 bpm and a correlation of 0∶98 was achieved with our method. These findings suggest that the proposed methodology is robust to motion artifacts and is therefore applicable for heart rate monitoring during sports and rehabilitation.