Quantification of Fractional Dynamical Stability of EEG Signals as a Bio-Marker for Cognitive Motor Control

Title

Quantification of Fractional Dynamical Stability of EEG Signals as a Bio-Marker for Cognitive Motor Control

 Author

Reed, Emily A. (University of Southern California)
Bogdan, Paul (University of Southern California)
Gonçalves Melo Pequito, S.D. (TU Delft Team Sergio Pequito)

Date

2022

 Abstract

Assessing the stability of biological system models has aided in uncovering a plethora of new insights in genetics, neuroscience, and medicine. In this paper, we focus on analyzing the stability of neurological signals, including electroencephalogram (EEG) signals. Interestingly, spatiotemporal discrete-time linear fractional-order systems (DTLFOS) have been shown to accurately and efficiently represent a variety of neurological and physiological signals. Here, we leverage the conditions for stability of DTLFOS to assess a real-world EEG data set. By analyzing the stability of EEG signals during movement and rest tasks, we provide evidence of the usefulness of the quantification of stability as a bio-marker for cognitive motor control.

 Subject

nonlinear models
stability
EEG signals
control applications
cognitive motor control

 To reference this document use:

http://resolver.tudelft.nl/uuid:f75e6d40-8c00-45c1-add8-399e7f06364f

 DOI

https://doi.org/10.3389/fcteg.2021.787747

 ISSN

2673-6268

 Source

Frontiers in Control Engineering, 2

 Part of collection

Institutional Repository

 Document type

journal article

 Rights

© 2022 Emily A. Reed, Paul Bogdan, S.D. Gonçalves Melo Pequito
Files
PDF fcteg_02_787747.pdf 3.19 MB
Close viewer