{'fraction_non_alphanumeric': 0.020338983050847456, 'fraction_numerical': 0.00423728813559322, 'mean_word_length': 5.119170984455959, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Estimation of heart rate from photoplethysmography during physical exercise using Wiener filtering and the phase vocoder

A system for estimation of the heart rate (HR) from the photoplethysmographic (PPG) signal during intensive physical exercises is presented. The Wiener filter is used to attenuate the noise introduced by the motion artifacts in the PPG signals. The frequency with the highest magnitude estimated using Fourier transformation is selected from the resultant de-noised signal. The phase vocoder technique is exploited to refine the frequency estimate, from which the HR in beats per minute (BPM) is finally calculated. On a publically available database of twenty three PPG recordings, the proposed technique obtains an error of 2.28 BPM. A relative error rate reduction of 18% is obtained when comparing with the state-of-the art PPG-based HR estimation methods. The proposed system is shown to be robust to strong motion artifact, produces high accuracy results and has very few free parameters, in contrast to other available approaches. The algorithm has low computational cost and can be used for fitness tracking and health monitoring in wearable devices.