Digital signal processing methods for the evaluation of Blood Volume Pulse (BVP) waveform changes due to exercise

Previous research by our group has revealed that the Blood Volume Pulse (BVP) waveform recorded using an infrared finger photoplethysmograph (PPG) undergoes changes as the subject performs physical exercise. In particular, a reduction in the depth of the Dicrotic Notch has been observed. There is an interest in characterizing those changes through a single parameter to measure the level of exercise the subject has reached, at any time during an exercise session. This paper reports on the comparison of three Digital Signal Processing approaches designed to reflect the BVP waveform changes through a single parameter, which could be obtained automatically from the digitized BVP signal. The first approach derives a single parameter from the distribution found in the average histogram of several time-aligned and averaged BVP beats. Our second approach analyzes the ratio observed between the first harmonic and higher harmonics in the BVP signal. The third approach evaluates the Dicrotic Notch depth directly from the BVP waveform, tracking sample values about the local minimum defined by the Dicrotic Notch. Our study, involving observations from 10 subjects, ranks these three approaches according to their ability to reflect the changes in BVP due to exercise.