Characterization of upper limb movement-related EEG dynamics through fractional integrated autoregressive modeling

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Cavaliere, L (Author) Other; Catrambone, V (Author) Other; Bianchi, M (Author) Other; Rocha, AP (Author) FCUP; Valenza, G (Author) Other

Conference proceedings International

Title: 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, Mexico, November 1-5, 2021

Pages: 5987-5990

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00W-0WT

DOI: 10.1109/embc46164.2021.9630051

Abstract (EN): The analysis of electroencephalographic (EEG) series associated with movement performance is important for understanding the cortical neural control on motor tasks. While the existence of long-range correlations in physiological dynamics has been reported in previous studies, such a characterization in EEG series gathered during upper-limb movements has not been performed yet. To this end, here we report on a fractional integrated autoregressive analysis of EEG series during different functional classes of motor actions and resting phase, and data were gathered from 33 healthy volunteers. Results show significant differences in EEG long-range correlations on EEG series from characteristic topography.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4