Recent designs of neural-machine interfaces (NMIs) incorporating electroencephalography (EEG) or electromyography (EMG) have been used in lower limb assistive devices. While the results of previous studies have shown promise, a NMI which takes advantage of early movement-related EEG activity preceding movement onset, as well as the improved signal-to-noise ratio of EMG, could prove to be more accurate and responsive than current NMI designs based solely on EEG or EMG. Previous studies have demonstrated that the activity of the sensorimotor cortex is coupled to the firing rate of motor units in lower limb muscles during voluntary contraction. However, the exploration of corticomuscular coherence during locomotive tasks has been limited. In this study, coupling between the motor cortex and right tibialis anterior muscle activity was preliminarily investigated during self-paced over-ground walking and ramp ascent. EEG at the motor cortex and surface EMG from the tibialis anterior were collected from one able-bodied subject. Coherence between the two signals was computed and studied across gait cycles. The EEG activity led the EMG activity in the low gamma band in swing phase of level ground walking and in stance phase of ramp ascent. These results may inform the future design of EEG-EMG multimodal NMIs for lower limb devices that assist locomotion of people with physical disabilities.
|Original language||English (US)|
|Number of pages||4|
|Journal||Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference|
|State||Published - Aug 2016|
- Journal Article