A novel PSWT-DTW approach for analyzing pseudo-periodic signals

Pseudo-periodic signals are rampant in biomedical applications but are difficult to analyze. One approach is to compute time domain parameters of each individual cycle in the pseudo-periodic signal. The classic approach requires repeated computation in each cycle, which tends to be either error prone, computationally burdensome, or requires manual effort. We provide a novel combination of the pitch synchronous wavelet transform which when combined with dynamic time warping results in effective quantification of cycles in the pseudo-periodic signal. We demonstrate our application of this method in studying the arterial pulse. The results show that our approach is feasible and effective, and confirms further scope in other applications.