Abstract
BackgroundBridging the gap between laboratory brain-computer interface (BCI) demonstrations and real-life applications has gained increasing attention nowadays in translational neuroscience. An urgent need is to explore the feasibility of using a low-cost, ease-of-use electroencephalogram (EEG) headset for monitoring individuals’ EEG signals in their natural head/body positions and movements. This study aimed to assess the feasibility of using a consumer-level EEG headset to realize an online steady-state visual-evoked potential (SSVEP)-based BCI during human walking.MethodsThis study adopted a 14-channel Emotiv EEG headset to implement a four-target online SSVEP decoding system, and included treadmill walking at the speeds of 0.45, 0.89, and 1.34 meters per second (m/s) to initiate the walking locomotion. Seventeen participants were instructed to perform the online BCI tasks while standing or walking on the treadmill. To maintain a constant viewing distance to the visual targets, participants held the hand-grip of the treadmill during the experiment. Along with online BCI performance, the concurrent SSVEP signals were recorded for offline assessment.ResultsDespite walking-related attenuation of SSVEPs, the online BCI obtained an information transfer rate (ITR) over 12 bits/min during slow walking (below 0.89 m/s).ConclusionsSSVEP-based BCI systems are deployable to users in treadmill walking that mimics natural walking rather than in highly-controlled laboratory settings. This study considerably promotes the use of a consumer-level EEG headset towards the real-life BCI applications.
Highlights
Bridging the gap between laboratory brain-computer interface (BCI) demonstrations and real-life applications has gained increasing attention nowadays in translational neuroscience
Since the treadmill walking protocol adopted in this study did not randomize the walking speeds, we cannot completely rule out the possibility that the visual- or motor-fatigue could contribute to the state visual-evoked potential (SSVEP) deterioration
The empirical results in this study demonstrated the applicability of using the consumer-level Emotiv headset to decode SSVEPs in moving humans, the obtained satisfactory performance might not assure that the headset could be perfectly suitable for all BCI applications
Summary
Bridging the gap between laboratory brain-computer interface (BCI) demonstrations and real-life applications has gained increasing attention nowadays in translational neuroscience. There might be significant differences in how the brain works in ecologically valid environments versus highly controlled laboratory environments [2,3]. Studies linking brain dynamics to cognitive functions have been majorly devoted to the stationary and tethered individuals, in which the participants underwent the experiments with highly-controlled settings in laboratories. They were usually instructed to avoid any task-irrelevant head/body movements. Studying the brain dynamics associated with naturalistic human behaviors is of great importance in translational neuroscience
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
