Online speech synthesis using a chronically implanted brain-computer interface in an individual with ALS.

Autor: Angrick M; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. mangric1@jhu.edu., Luo S; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Rabbani Q; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA., Candrea DN; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Shah S; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Milsap GW; Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA., Anderson WS; Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Gordon CR; Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Section of Neuroplastic and Reconstructive Surgery, Department of Plastic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Rosenblatt KR; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Department of Anesthesiology & Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Clawson L; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Tippett DC; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Department of Otolaryngology-Head and Neck Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Maragakis N; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Tenore FV; Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA., Fifer MS; Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA., Hermansky H; Center for Language and Speech Processing, The Johns Hopkins University, Baltimore, MD, USA.; Human Language Technology Center of Excellence, The Johns Hopkins University, Baltimore, MD, USA., Ramsey NF; UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands., Crone NE; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. ncrone@jhmi.edu.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 Apr 26; Vol. 14 (1), pp. 9617. Date of Electronic Publication: 2024 Apr 26.
DOI: 10.1038/s41598-024-60277-2
Abstrakt: Brain-computer interfaces (BCIs) that reconstruct and synthesize speech using brain activity recorded with intracranial electrodes may pave the way toward novel communication interfaces for people who have lost their ability to speak, or who are at high risk of losing this ability, due to neurological disorders. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a man with impaired articulation due to ALS, participating in a clinical trial (ClinicalTrials.gov, NCT03567213) exploring different strategies for BCI communication. The 3-stage approach reported here relies on recurrent neural networks to identify, decode and synthesize speech from electrocorticographic (ECoG) signals acquired across motor, premotor and somatosensory cortices. We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the participant from a vocabulary of 6 keywords previously used for decoding commands to control a communication board. Evaluation of the intelligibility of the synthesized speech indicates that 80% of the words can be correctly recognized by human listeners. Our results show that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words while preserving the participant's voice profile, and provide further evidence for the stability of ECoG for speech-based BCIs.
(© 2024. The Author(s).)
Databáze: MEDLINE
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