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

Abstract

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.INDEX TERMS Correlation distribution, exoskeleton-assisted overground walking, electroencephalogram (EEG), electromyogram (EMG), naturalistic overground walking, power spectral density (PSD).The associate editor coordinating the review of this manuscript and approving it for publication was Zehong Cao .

Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review

“…The distribution of papers in the categories is shown in a pie chart in Figure 4. Study of the cortico-muscular coupling (1) during motor tasks [37][38][39][40][41] and (2) with electrical stimulation [42][43][44][45][46] Investigation of the effects of exoskeleton on functional connectivity [47][48][49] Investigation of the effects of visual feedback [50,51] Detection of movement intention [52,53] Study of the interhemispheric interaction with TMS [54] Study of a neurophysiological marker of stress [55] Study of slow cortical potentials in stroke [56] Study of correlation between lower back pain and altered postural stabilization [57] Test new rehabilitation paradigm [34,[58][59][60][61][62] Investigation of the efficacy of BMI [63] and EEG feedback [64] Table 1. Type of study and aim.…”

“…Cortico-muscular coherence was also tested as a tool for investigating the effects of functional electrical stimulation [42][43][44][45][46]. Some studies analyzed the effects of treatments based on exoskeletons on neuromotor outcomes [47][48][49]. The efficacy of visual feedback was assessed to explore novel rehabilitation paradigms [50,51].…”

Surface Electromyography and Electroencephalogram-Based Gait Phase Recognition and Correlations Between Cortical and Locomotor Muscle in the Seven Gait Phases

“…Therefore, we predict the gait phases at three speeds. Secondly, we calculated TFCMI values between beta-band EEG and sEMG channels in the seven gait phases to research the theoretical basis of gait phase recognition based on EEG and sEMG (Oliveira et al, 2018;Li et al, 2019).…”

Correlations between Cortical and Locomotor Muscle in the Seven Gait Phases during Treadmill Walking

“…We have previously used these signals to identify the movement intentions of the human body and have applied them to rehabilitation devices [28] [29]. In this study, we calculated TFCMI values between EEG and sEMG channels in the seven gait phases, using both beta and gamma band EEG data, following previous research [30] [31].…”