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What Are Spectral and Spatial Distributions of EEG-EMG Correlations in Overground Walking? An Exploratory Study

Li, Junhua and Dimitrakopoulos, Georgios N and Thangavel, Pavithra and Chen, Gong and Sun, Yu and Guo, Zhao and Yu, Haoyong and Thakor, Nitish and Bezerianos, Anastasios (2019) 'What Are Spectral and Spatial Distributions of EEG-EMG Correlations in Overground Walking? An Exploratory Study.' IEEE Access, 7. 143935 - 143946. ISSN 2169-3536

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You probably believe that a latent relationship between the brain and lower limbs exists and it varies across different walking conditions (e.g., walking with or without an exoskeleton). Have you ever thought what the distributions of measured signals are? To address this question, we simultaneously collected electroencephalogram (EEG) and electromyogram (EMG) signals while healthy participants were conducting four overground walking conditions without any constraints (e.g., specific speed). The EEG results demonstrated that a wide range of frequencies from delta band to gamma band were involved in walking. The EEG power spectral density (PSD) was significantly different in sensorimotor and posterior parietal areas between exoskeleton-assisted walking and non-exoskeleton walking. The EMG PSD difference was predominantly observed in the theta band and the gastrocnemius lateralis muscle. EEG-EMG PSD correlations differed among walking conditions. The alpha and beta bands were primarily involved in consistently increasing EEG-EMG PSD correlations across the walking conditions, while the theta band was primarily involved in consistently decreasing correlations as observed in the EEG involvement. However, there is no dominant frequency band as observed in the EMG involvement. Channels located over the sensorimotor area were primarily involved in consistently decreasing EEG-EMG PSD correlations and the outer-ring channels were involved in the increasing EEG-EMG PSD correlations. Our study revealed the spectral and spatial distributions relevant to overground walking and deepened the understanding of EEG and EMG representations during locomotion, which may inform the development of a more human-compatible exoskeleton and its usage in motor rehabilitation.

Item Type: Article
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 16 Oct 2019 14:24
Last Modified: 16 Oct 2019 14:24

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