A novel approach for features extraction in physiological signals

The authors have investigated a novel processing technique, which allows to measure possibly relevant features in the ECG (Electrocardiogram) signal according to the morphology of its waveform. The aim of this work is to prove its efficacy in the assessment of the subject's Heart Rate (HR) and to broaden its use to signals coming from different biomedical sensors (based on optical, acoustical and mechanical principles) for the computation of HR. The analysis technique proposed for the identification of the main feature (R-peak) in ECG signal provides results that are comparable to those obtained with traditional approaches. The approach has also been applied to other signals related to blood flow, such as PCG (Phonocardiography), PPG (Photoplethysmography) and VCG (Vibrocardiography), where standard algorithms (i.e. Pan & Tompkins) could not be widely applied. HR results from a measurement campaign on 8 healthy subjects have shown, respect to ECG, a deviation (calculated as 2σ) of ±3.3 bpm, ±2.3 bpm and ±1.5 bpm for PCG, PPG and VCG. Future work will involve the extraction of additional features from the previous signals, with the aim of a deeper characterization of them to better describe the subject's health status.