Motion artifact reduction from PPG signals during intense exercise using filtered X-LMS

Abstract

Photoplethysomographic (PPG) signal is crucial for non-invasive monitoring of heart rate. It is acquired by using pulse oximeter that are prone to artifacts. A major application of this technique is monitoring the heart rate during physical exertion. Extraction of heart rate (HR) from the PPG in this case is difficult due to the strong motion related artifacts. This paper proposes an efficient method based on a reference generation using singular value decomposition and then multistage application of filtered X-LMS for removing motion artifacts from PPG signal. Simultaneous three-axis acceleration data is acquired and used as reference signal to measure time and extent of motion artifact in PPG signal. This is followed by an application of Slope Sum Method (SSM) to track peaks, and thus determine the heart rate. Testing of proposed method on PPG signals acquired from multiple subjects performing intense exercises (jogging at an average speed of 12 km/hour), results in mean absolute error of 1.37 beats per minute (BPM). Moreover, it is shown that proposed algorithm is robust to excessive occurrence of motion artifacts.