Asynchronous decoding of finger movements from ECoG signals using long-range dependencies conditional random fields

Delgado Saa, Jaime Fernando and De Pesters, Adriana and Çetin, Müjdat (2016) Asynchronous decoding of finger movements from ECoG signals using long-range dependencies conditional random fields. Journal of Neural Engineering, 13 (3). ISSN 1741-2560 (Print) 1741-2552 (Online)

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Abstract

Objective. In this work we propose the use of conditional random fields with long-range dependencies for the classification of finger movements from electrocorticographic recordings. Approach. The proposed method uses long-range dependencies taking into consideration time-lags between the brain activity and the execution of the motor task. In addition, the proposed method models the dynamics of the task executed by the subject and uses information about these dynamics as prior information during the classification stage. Main results. The results show that incorporating temporal information about the executed task as well as incorporating long-range dependencies between the brain signals and the labels effectively increases the system's classification performance compared to methods in the state of art. Significance. The method proposed in this work makes use of probabilistic graphical models to incorporate temporal information in the classification of finger movements from electrocorticographic recordings. The proposed method highlights the importance of including prior information about the task that the subjects execute. As the results show, the combination of these two features effectively produce a significant improvement of the system's classification performance.
Item Type: Article
Uncontrolled Keywords: Brain-computer interfaces; ECoG; synchronous classification; temporal dynamics; probabilistic graphical models
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QP Physiology > QP1-(981) Physiology > QP351-495 Neurophysiology and neuropsychology
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Müjdat Çetin
Date Deposited: 12 Nov 2016 13:45
Last Modified: 22 May 2019 13:43
URI: https://research.sabanciuniv.edu/id/eprint/30316

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