Faculty Collaboration Database

Phase modulation-based response-inhibition outcome prediction in translational scenario of stop-signal task. Annu Int Conf IEEE Eng Med Biol Soc 2016 Aug;2016:5857-5860

Date

03/09/2017

Pubmed ID

28269586

DOI

10.1109/EMBC.2016.7592060

Scopus ID

2-s2.0-85009083912 (requires institutional sign-in at Scopus site)   1 Citation

Abstract

In this paper, a method is proposed to predict the resting-state outcomes of participants based on their electroencephalogram (EEG) signals recorded before the successful /unsuccessful response inhibition. The motivation of this study is to enhance the shooter performance for shooting the target, when their EEG patterns show that they are ready. This method can be used in brain-computer interface (BCI) system. In this study, multi-channel EEG from twenty participants are collected by the electrodes placed at different scalp locations in resting-state time. The EEG trials are used to predict two possible outcomes: successful or unsuccessful stop. Four classifiers (QDC, KNNC, PARZENDC, LDC) are used in this study to evaluation the accuracy of our system. Based on the collected time-domain EEG signals, the phase locking value (PLV) from 5-pair electrodes are calculated and then used as the feature input for the classifiers. Our experimental results show that the proposed method prediction accuracy (leave-one-out) was obtained 95% by QDC classifier.

Author List

Chikara RK, Li-Wei Ko

Author

Rupesh Chikara PhD Postdoctoral Fellow in the Neurology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Adult
Brain-Computer Interfaces
Discriminant Analysis
Electrodes
Electroencephalography
Healthy Volunteers
Humans
Male
Photic Stimulation
Reaction Time
Young Adult