Volume 18, No. 6, 2021
Effective Heart Rate Estimation From PPG Signal By Fuzzy Wavelet Approach
Ameena Firdous Nikhat , Dr Shameem Akhter
Abstract
Wrist wearable devices have become part of one’s daily requirement to track an individual’s heart rate, to keep a track of various health-related disorders. While a person is, exercising his heart rate may shoot up and give a false value due to the motion artefacts associated with it. Our main aim here is to reduce the motion artefacts to give an accurate heart rate. The PPG signal emits light, which is absorbed by the skin and a photodiode, which records all the changes in the bloodstream. PPG signal extracted from the photodiode is corrupted by the motion artefacts many algorithms are proposed to lessen motion artifacts we have proposed a deep learning technique to lessen the motion artefacts and denoising PPG signals. The PPG signal is extracted from the ECG signal considering a dataset, which is further preprocessed to clean the contaminated PPG signal. Denoising the PPG signal as a well-performing spectral examination to get a clean PPG signal. We perform feature extraction where all the necessary information is extracted and processed. PPG is extensively used owing to its being economical. Research is being done to extend the features of PPG to find the respiration rate, blood oxygen saturation. PPG signals work as a good alternative to ECG signals however, ECG signals give accurate values. We try to increase the effectiveness of our model to give accurate estimations for the detection of heart rate. The growth of wearable wrist devices has led to the innovation of acquiring clinical data.
Pages: 1800-1815
Keywords: PPG, ECG, Denoising, Motion Artifacts.