Self-paced silent speech brain-computer interface for device control
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.
Related
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- Volitional control of a recurrent brain computer interface via covert reinforcement of endogenous reward networks
- A Dataset with Bilingual TV Commands for Silent Speech Interfaces Using Electroencephalographic Signals
- Brain-writing-BERT for generalizable handwriting brain-computer interface
- From Neurons to Conversation: Speech Brain-Computer Interfaces
BibTeX
@article{luo2026selfpaced,
title = {{Self-paced silent speech brain-computer interface for device control}},
author = {Shiyu Luo and Miguel Angrick and Christopher Coogan and Daniel N. Candrea and Kimberley Wyse-Sookoo and Anouck Schippers and Rohit Ganji and Griffin W. Milsap and William S. Anderson and Chad R. Gordon and Donna C. Tippett and Nicholas J. Maragakis and Lora L. Clawson and Mariska J. Vansteensel and Francesco V. Tenore and Hynek Hermansky and Matthew S. Fifer and Nick F. Ramsey and Nathan E. Crone},
journal = {Communications Biology},
year = {2026},
month = nov,
doi = {10.1038/s42003-026-10477-5},
url = {https://www.nature.com/articles/s42003-026-10477-5},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Self-paced silent speech brain-computer interface for device control
AU - Shiyu Luo
AU - Miguel Angrick
AU - Christopher Coogan
AU - Daniel N. Candrea
AU - Kimberley Wyse-Sookoo
AU - Anouck Schippers
AU - Rohit Ganji
AU - Griffin W. Milsap
AU - William S. Anderson
AU - Chad R. Gordon
AU - Donna C. Tippett
AU - Nicholas J. Maragakis
AU - Lora L. Clawson
AU - Mariska J. Vansteensel
AU - Francesco V. Tenore
AU - Hynek Hermansky
AU - Matthew S. Fifer
AU - Nick F. Ramsey
AU - Nathan E. Crone
PY - 2026
DA - 2026/11/11
JO - Communications Biology
DO - 10.1038/s42003-026-10477-5
UR - https://www.nature.com/articles/s42003-026-10477-5
AB - 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.
SN - 2399-3642
ER -