Faster Gait Speeds Reduce Alpha and Beta EEG Spectral Power From Human Sensorimotor Cortex.

Area of Science:

• Neuroscience
• Biomechanics
• Signal Processing

Background:

• Assessing human sensorimotor electrocortical dynamics during locomotion is challenging due to motion and muscle artifacts in electroencephalography (EEG).
• Existing artifact removal methods may obscure genuine neural signals related to gait.
• Novel mobile EEG techniques are needed to accurately capture brain activity during dynamic movements like walking.

Purpose of the Study:

• To investigate the effect of walking speed on human sensorimotor electrocortical dynamics.
• To compare artifact removal strategies for mobile high-density EEG during treadmill walking.
• To validate the utility of dual-layer EEG electrodes and electromyographic (EMG) signal processing for isolating neural activity.

Main Methods:

• Employed mobile high-density electroencephalography (EEG) with novel dual-layer electrodes to simultaneously record brain activity and motion artifacts.
• Integrated electromyographic (EMG) recordings from the neck to identify and remove muscle artifacts.
• Compared various artifact removal techniques during treadmill walking at four distinct speeds (0.5, 1.0, 1.5, and 2.0 m/s).

Main Results:

• Sensorimotor alpha and beta spectral power exhibited distinct patterns across the gait cycle, varying with limb phase and walking speed.
• Faster walking speeds were associated with less pronounced sensorimotor spectral power fluctuations and reduced overall alpha and beta power.
• Neck EMG and isolated noise recordings confirmed gait events and showed increased spectral power at higher walking speeds, validating artifact isolation.

Conclusions:

• Dual-layer EEG effectively isolates sensorimotor electrocortical dynamics changes across different walking speeds.
• While common and novel artifact rejection methods showed similar intrastride cortical fluctuations, dual-layer EEG confirmed the removal of residual artifacts.
• This study demonstrates that dual-layer EEG and integrated EMG processing enable accurate characterization of neural activity during walking and reveal speed-dependent modulations in sensorimotor dynamics.