With the development of smart phones and photoplethysmography sensors, human health can be monitored continuously. A photoplethysmograph is a signal (referred to as PPG signal) acquired with photoplethysmography and can be used to evaluate blood pressure, blood oxygen saturation, heart rate and heart rate variability parameters (referred to as HRV). Because photoplethysmography and HRV parameters are sensitive to noise from the surroundings and can easily be corrupted, we decided to check the validity of HRV parameters calculated from PPG signal (referred to as PRV). Four methods for signal preprocessing and three methods for systolic peak identification were chosen from the literature. Through simulations the best three combinations of signal preprocessing methods and peak identifying methods were chosen and applied to real life data. The main conclusion presented in our work is that we successfully evaluated heart rate from PPG signal, while other PRV parameters were not valid compared to true values of HRV parameters.
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