When interpolation-induced reflection artifact meets time-frequency analysis

TL;DR

This paper investigates the reflection artifact caused by interpolation in time-frequency analysis of biomedical signals, providing theoretical insights and practical examples, emphasizing the importance of proper interpolation to avoid misleading artifacts.

Contribution

It formulates the reflection effect problem, offers a theoretical justification, and demonstrates its practical impact in biomedical data analysis.

Findings

Reflection artifacts are theoretically justified and practically observed.

Artifacts significantly affect time-frequency analysis of biomedical signals.

Proper interpolation schemes are essential to mitigate reflection artifacts.

Abstract

While extracting the temporal dynamical features based on the time-frequency analyses, like the reassignment and synchrosqueezing transform, attracts more and more interest in bio-medical data analysis, we should be careful about artifacts generated by interpolation schemes, in particular when the sampling rate is not significantly higher than the frequency of the oscillatory component we are interested in. In this study, we formulate the problem called the reflection effect and provide a theoretical justification of the statement. We also show examples in the anesthetic depth analysis with clear but undesirable artifacts. The results show that the artifact associated with the reflection effect exists not only theoretically but practically. Its influence is pronounced when we apply the time-frequency analyses to extract the time-varying dynamics hidden inside the signal. In conclusion, we have to carefully deal with the artifact associated with the reflection effect by choosing a proper interpolation scheme.