Extraction of single-trial cortical beta oscillatory activities in EEG signals using empirical mode decomposition

NCUIR > College of Electrical Engineering & Computer Science > Department of Electrical Engineering > journal & Dissertation > Item 987654321/51941

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51941

Title:	Extraction of single-trial cortical beta oscillatory activities in EEG signals using empirical mode decomposition
Authors:	Yeh,CL;Chang,HC;Wu,CH;Lee,PL
Contributors:	電機工程學系
Keywords:	EVENT-RELATED DESYNCHRONIZATION;PARKINSONS-DISEASE;SPECTRAL-ANALYSIS;MOVEMENT;SYNCHRONIZATION;BRAIN;MEG;CLASSIFICATION;STIMULUS;TASK
Date:	2010
Issue Date:	2012-03-28 10:11:07 (UTC+8)
Publisher:	國立中央大學
Abstract:	Background: Brain oscillatory activities are stochastic and non-linearly dynamic, due to their non-phase-locked nature and inter-trial variability. Non-phase-locked rhythmic signals can vary from trial-to-trial dependent upon variations in a subject's performance and state, which may be linked to fluctuations in expectation, attention, arousal, and task strategy. Therefore, a method that permits the extraction of the oscillatory signal on a single-trial basis is important for the study of subtle brain dynamics, which can be used as probes to study neurophysiology in normal brain and pathophysiology in the diseased. Methods: This paper presents an empirical mode decomposition (EMD)-based spatiotemporal approach to extract neural oscillatory activities from multi-channel electroencephalograph (EEG) data. The efficacy of this approach manifests in extracting single-trial post-movement beta activities when performing a right index-finger lifting task. In each single trial, an EEG epoch recorded at the channel of interest (CI) was first separated into a number of intrinsic mode functions (IMFs). Sensorimotor-related oscillatory activities were reconstructed from sensorimotor-related IMFs chosen by a spatial map matching process. Post-movement beta activities were acquired by band-pass filtering the sensorimotor-related oscillatory activities within a trial-specific beta band. Signal envelopes of post-movement beta activities were detected using amplitude modulation (AM) method to obtain post-movement beta event-related synchronization (PM-bERS). The maximum amplitude in the PM-bERS within the post-movement period was subtracted by the mean amplitude of the reference period to find the single-trial beta rebound (BR). Results: The results showed single-trial BRs computed by the current method were significantly higher than those obtained from conventional average method (P < 0.01; matched-pair Wilcoxon test). The proposed method provides high signal-to-noise ratio (SNR) through an EMD-based decomposition and reconstruction process, which enables event-related oscillatory activities to be examined on a single-trial basis. Conclusions: The EMD-based method is effective for artefact removal and extracting reliable neural features of non-phase-locked oscillatory activities in multi-channel EEG data. The high extraction rate of the proposed method enables the trial-by-trial variability of oscillatory activities can be examined, which provide a possibility for future profound study of subtle brain dynamics.
Relation:	BIOMEDICAL ENGINEERING ONLINE
Appears in Collections:	[Department of Electrical Engineering] journal & Dissertation

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