Preliminary EEG Characterisation of Intention to Stand and Walk for Exoskeleton Applications

Abstract

Wearable lower limb exoskeletons aim to mobilize and improve the quality of life of people with lower limb paralysis. However, all the current commercially available exoskeletons require good upper limb function to operate them effectively. This limits their use for people with higher-level impairments, such as tetraplegia. In this paper we investigate the possibility of being able to decode from the user’s brain signals, their intention to perform various actions, including standing up and walking, with a view to eventually controlling an exoskeleton with a brain-computer interface. As such, we present some preliminary results that show statistically significant changes in Mu band power, when preparing to execute movements and during the execution of movements.