Self-paced silent speech brain-computer interface for device control

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Abstract
Brain-computer interfaces can potentially restore autonomy to people with paralysis, including the ability to control their own environment via smart devices in the home. BCI applications for controlling smart devices to date have required visual displays or auditory cues, limiting the user’s ability to autonomously and privately issue commands. In this study, a clinical trial participant with amyotrophic lateral sclerosis (ALS) used a chronically implanted electrocorticographic (ECoG) BCI to control smart devices with self-paced silent speech commands. Across 18 experimental sessions, silently mimed speech commands were detected in real time and decoded with a median accuracy of 97.1% (chance: 7.14%) and the median correct decodes per minute was 11.86. These results demonstrate that silently attempted speech can be reliably decoded without exogenous timing cues, supporting the feasibility of reliable autonomous smart device control with an implantable BCI.
Funding Information
  • National Institute of Neurological Disorders and Stroke (UHSNS114439)