Scientific impact of the standard phase reconstruction method and its clinical applications

Phase is the most fundamental physical quantity when we study an oscillatory time series, and there are a lot of tools aiming to estimate phase. Most existing tools are developed based on the well-developed analytic function model. Unfortunately, this approach might not be suitable for several modern signals, particularly biomedical signals, due to the intrinsic complicated structure, and the lack of standard methods on how to estimate phases. Specifically, different recording equipment for the same physiological system might lead to different phases based on existing tools, and the same recording equipment for different subjects might vary from subject to subject, even if the cycling periods are the same. The lack of consensus, or standard, might lead to the challenge of reproducibility, communication, and scientific interpretation. In face of this challenge, we propose the use of the recently developed adaptive non-harmonic model and synchrosqueezing transformation to standardize the phase information extraction. To illustrate the scientific impact of the proposed standardization and tools, we show analysis results in two different physiological signals with clinical applications.