Real-time estimation of phase and amplitude with application to neural data

Autor:	Rosenblum, Michael, Pikovsky, Arkady, Kühn, Andrea A., Busch, Johannes L.
Rok vydání:	2021
Předmět:	Quantitative Biology - Neurons and Cognition Electrical Engineering and Systems Science - Signal Processing
Druh dokumentu:	Working Paper
Popis:	Computation of the instantaneous phase and amplitude via the Hilbert Transform is a powerful tool of data analysis. This approach finds many applications in various science and engineering branches but is not proper for causal estimation because it requires knowledge of the signal's past and future. However, several problems require real-time estimation of phase and amplitude; an illustrative example is phase-locked or amplitude-dependent stimulation in neuroscience. In this paper, we discuss and compare three causal algorithms that do not rely on the Hilbert Transform but exploit well-known physical phenomena, the synchronization and the resonance. After testing the algorithms on a synthetic data set, we illustrate their performance computing phase and amplitude for the accelerometer tremor measurements and a Parkinsonian patient's beta-band brain activity. Comment: 11 pages, 5 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2105.10404 Zobrazit plný text záznamu View this record from Arxiv