LAUSR

Robustness of estimating cardiorespiratory parameters from photoplethysmography (PPG) signal is highly dependent on the quality of the signal, which is heavily affected by motion artifacts. To increase the estimation accuracy of cardiorespiratory parameters, this article describes a novel fusion method to efficiently and effectively reduce the motion artifacts from the acquired PPG signal. The proposed fusion technique requires simultaneously acquiring data from a PPG sensor and accelerometer. To filter out the frequencies associated with motion, the method uses stopband filters with a central rejection frequency and bandwidth determined by the output signal of the accelerometer. Under such conditions, the proposed method to remove the motion artifacts does not depend on the quality of the reference signal and has almost no impact on the nature of PPG signals (i.e., amplitude, baseline, and periodicity). The effectiveness of the proposed method in the suppression of in-band and out-of-band frequencies of motion is numerically and experimentally evaluated. It is shown that the filtered PPG signal has sufficient information to estimate different cardiac parameters such as heart- (HR), respiration rate (RR), and blood oxygen saturation (SpO2). The motion artifact-free PPG signal obtained using our proposed method can estimate HR, RR, and SpO2 with an accuracy of above 95%. This level of accuracy confirms the usefulness of the proposed fusion method for accuracy improvement of cardiorespiratory parameters monitored by the filtered PPG signal.