Investigation of Theta Rhythm Effect in Detection of Finger Movement. (February 2019)

• Record Type: Journal Article
• Authors: Ketenci, Seniha; Kayikcioglu, Temel
• Is Part Of: Journal of experimental neuroscience. Volume 13(2019)
• Publication Date: 2019-02
• Subjects: EEG -- finger extension movement -- power spectral density -- theta rhythm; Neurosciences -- Periodicals; Nervous system -- Periodicals; Nervous System Diseases; Neurosciences; Nervous system; Neurosciences; Periodicals; Electronic journals; Periodicals; 573.8
• DOI: 10.1177/1179069519828737
• Languages: English
• ISSNs: 1179-0695

Abstract

Movements cause changes in cortical rhythms emanating from the sensorimotor area. It is known that alpha and beta brainwaves take an important role of motor activity and motor imagery. Besides, theta rhythm is considered to carry substantial information about movement initiation and execution. In this study, effect of theta brainwave on movement detection was investigated in four-right handed participants who performed extensions with fingers of right hand using electroencephalography (EEG). Movement and rest epochs from continuous EEG record were extracted using muscle signals. Channels located over sensorimotor area were selected and referenced according to common average and Laplacian reference methods. Power spectral density function was used to display existence of theta band in frequency domain. To analyze theta, alpha and beta rhythms of the epochs individually and together, we filtered them to their interval range with Butterworth bandpass infinite filter before feature extraction and classification stages. Then, principal component analysis and Hjorth parameters were chosen to extract efficient features in the study aiming to investigate the effect of theta brainwaves on finger movement detection. According to classification accuracies using support vector machine classifier, alpha, beta, theta rhythms and also their different combinations were compared with each other. The performance of the epochs including alpha, beta and theta rhythms were the best and they were classified ~2% to 4% higher value in accuracy than the signals including only alpha and beta rhythms. According to this, it has proved that theta brainwave takes a role and makes contribution to motor activity.