Abstract
PurposeP300 component of event related potentials in response to visual and auditory stimulation has been widely used in brain–computer interfaces (BCI). In clinical applications, tactile stimulus based on somatosensory electrical stimulation is an alternative for patients with impaired vision or hearing. This study presents an online P300 BCI based on somatosensory electrical stimulation paradigm. P300 signals were elicited by tactile selective attention of electrical stimuli on four fingers.MethodsFifteen healthy subjects participated in this study. Participants’ task was to focus their attention on the target finger and count the number. The classification of P300 signals was performed by step-wise linear discriminate analysis.ResultsThe average classification accuracy of the somatosensory BCI was 79.81 ± 7.91%, with the information transfer rate at 4.9 ± 1.3 bits/min. The BCI performance on different time windows was also evaluated in the present study.ConclusionsOur results demonstrate the feasibility of employing somatosensory electrical stimuli to build a practical online P300 BCI without taxing the visual and auditory channel, providing a wider application prospect in clinical applications and daily life. We anticipate our diagram to be a starting point for more explorations on utilizing electrical somatosensory stimuli in conjunction with portable BCI for neural rehabilitation.
Highlights
Brain computer interfaces (BCIs) enable users to set up bidirectional connections between the world and their minds by translating the brain signals into computer control commands and sending back feedback signals [1,2,3]
The somatosensory event-related potentials (ERPs) elicited by target stimuli presented later latency and higher P300 amplitude than that elicited by non-target stimuli
An online BCI system based on electrical somatosensory stimulation was proposed
Summary
Brain computer interfaces (BCIs) enable users to set up bidirectional connections between the world and their minds by translating the brain signals into computer control commands and sending back feedback signals [1,2,3]. BCIs have attracted growing attention from researchers for studying, mapping, enhancing, and repairing human cognitive, sensory and motor functions [4]. Due to its non-invasiveness and relatively high communication speed, BCIs based on electroencephalogram (EEG) have become one of the popular choices. Among all kinds of EEG potentials suitable for BCIs, the P300 wave is a positive EEG deflection in the human event-related potentials (ERPs) which occurs around 300 ms after the target stimulus has been presented. Over the past several decades, P300 s are still popular to drive BCI systems since they are relatively robust and reliable [5]. The vast majority of P300 based BCI systems have used visual and sometimes auditory stimuli to elicit P300 potentials [6,7,8,9]. Though the fundamental research on ERPs mainly focuses on visual and auditory elicited
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