Classification of Emerging Neural Activity from Planning to Grasp Execution using a Novel EEG-Based BCI Platform

Autor:	Cetera, Anna, Rabiee, Ali, Ghafoori, Sima, Abiri, Reza
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Signal Processing Quantitative Biology - Neurons and Cognition
Druh dokumentu:	Working Paper
Popis:	There have been different reports of developing Brain-Computer Interface (BCI) platforms to investigate the noninvasive electroencephalography (EEG) signals associated with plan-to-grasp tasks in humans. However, these reports were unable to clearly show evidence of emerging neural activity from the planning (observation) phase - dominated by the vision cortices - to grasp execution - dominated by the motor cortices. In this study, we developed a novel vision-based grasping BCI platform that distinguishes different grip types (power and precision) through the phases of plan-to-grasp tasks using EEG signals. Using our platform and extracting features from Filter Bank Common Spatial Patterns (FBCSP), we show that frequency-band specific EEG contains discriminative spatial patterns present in both the observation and movement phases. Support Vector Machine (SVM) classification (power vs precision) yielded high accuracy percentages of 74% and 68% for the observation and movement phases in the alpha band, respectively. Comment: 4 pages, 4 figures, 1 table, conference paper
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.03493 Zobrazit plný text záznamu View this record from Arxiv