| Home > Publications Database > Real-time phase and amplitude estimation of neurophysiological signals exploiting a non-resonant oscillator. |
| Journal Article | DZNE-2021-01331 |
; ; ;
2022
Academic Press
Orlando, Fla.
This record in other databases:
Please use a persistent id in citations: doi:10.1016/j.expneurol.2021.113869
Abstract: A recent advancement in the field of neuromodulation is to adapt stimulation parameters according to pre-specified biomarkers tracked in real-time. These markers comprise short and transient signal features, such as bursts of elevated band power. To capture these features, instantaneous measures of phase and/or amplitude are employed, which inform stimulation adjustment with high temporal specificity. For adaptive neuromodulation it is therefore necessary to precisely estimate a signal's phase and amplitude with minimum delay and in a causal way, i.e. without depending on future parts of the signal. Here we demonstrate a method that utilizes oscillation theory to estimate phase and amplitude in real-time and compare it to a recently proposed causal modification of the Hilbert transform. By simulating real-time processing of human LFP data, we show that our approach almost perfectly tracks offline phase and amplitude with minimum delay and is computationally highly efficient.
Keyword(s): Adult (MeSH) ; Aged (MeSH) ; Brain: physiology (MeSH) ; Computer Simulation (MeSH) ; Deep Brain Stimulation: methods (MeSH) ; Female (MeSH) ; Humans (MeSH) ; Male (MeSH) ; Middle Aged (MeSH) ; Parkinson Disease: therapy (MeSH) ; Signal Processing, Computer-Assisted (MeSH) ; Amplitude ; Closed-loop deep brain stimulation ; Phase ; Real-time
|
The record appears in these collections: |