Fuzzy entropy based motion artifact detection and pulse rate estimation for fingertip photoplethysmography

The paper presents a fingertip photoplethysmography (PPG) based technique to estimate the pulse rate of the subject. The PPG signal obtained from a pulse oximeter is used for the analysis. The input samples are corrupted with motion artifacts due to minor motion of the subjects. Entropy measure of the input samples is used to detect the motion artifacts and estimate the pulse rate. A three step methodology is adapted to identify and classify signal peaks as true systolic peaks or artifact. CapnoBase database and CSL Benchmark database are used to analyze the technique and pulse rate estimation was performed with positive predictive value and sensitivity figures of 99.84% and 99.32% respectively for CapnoBase and 98.83% and 98.84% for CSL database respectively.