Utilization of adaptive-coefficient estimation method for Motion artifacts reduction from photoplethysmographic signals

Modern pulse oximeters are employed in critical care units to measure the vital medical parameters like heart rate and blood oxygen saturation levels. These devices work by acquiring the photoplethysmographic (PPG) data utilizing PPG sensors attached to finger/earlobe/forehead of the patient and then computing the ratio of amplitudes of the red and IR PPG signals. Further the ratio of amplitudes is used to estimate oxygen saturation levels with the help of calibration curve. Patient movements while recording the pulse oximeter data may result in erroneous estimation of medical data and may result in wrong diagnosis by the clinician. Data corruption in recorded PPG signals is referred as Motion artifact (MA) corruption and its detection and reduction is a crucial problem for most of the researchers. It is clear evident that detection and reduction of MA component from recorded PPG data by any signal processing technique may guarantee error-free estimation of oxygen saturation in arterial blood (SpO2). In this work, we present a adaptive coefficient estimation technique to detect MA components from quasi periodic natured PPG signal and then deduce MA reduced PPG signal. Fourier coefficients are estimated using basic least mean squares algorithm. The novelty of the proposed technique lies in detection and reduction of MA noise by estimating the Fourier coefficients and then based on randomness measures considering only the required number of Fourier coefficients dynamically to generate MA reduced PPG signal. SpO2 is estimated from MA reduced PPGs by utilizing the calibration curve. The superiority of proposed technique is been proved by comparing the experimental results with results obtained using basic least mean squares (LMS) method. PPG data recorded with different MA (Vertical, Horizontal and Bending movements of patient's finger) is considered for experiment analysis. Obtained SpO2 parameter calculations proved the efficacy of estimation technique in measurement of reliable and accurate SpO2, helpful for medical diagnosis.