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An Accurate and Rapidly Calibrating Speech Neuroprosthesis. | LitMetric

An Accurate and Rapidly Calibrating Speech Neuroprosthesis.

N Engl J Med

From the Departments of Neurological Surgery (N.S.C., M.W., C.I., X.H., T.S.-C., M.V.N., A.S., K.S., S.D.S., D.M.B.), Computer Science (X.H., M.V.N.), and Biomedical Engineering (T.S.-C., A.S.), University of California, Davis, Davis, and the Departments of Neurosurgery (D.R.D., E.Y.C., J.M.H.), Electrical Engineering (E.M.K.), and Computer Science (C.F.), the Wu Tsai Neurosciences Institute (E.M.K., J.M.H.), the Howard Hughes Medical Institute (F.R.W.), and Bio-X (J.M.H.), Stanford University, Stanford - both in California; the Departments of Radiology and Neuroscience, Washington University School of Medicine, Saint Louis (M.F.G.); the School of Engineering and Carney Institute for Brain Sciences, Brown University (L.R.H.), and the Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs Office of Rehabilitation Research and Development, VA Providence Healthcare (L.R.H.) - both in Providence, RI; and the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.R.H.).

Published: August 2024

AI Article Synopsis

  • Brain-computer interfaces can help individuals with paralysis communicate by translating their brain activity into text, but they often require extensive training and have limited accuracy.
  • A 45-year-old man with ALS had four microelectrode arrays implanted in his brain and was able to communicate through a neuroprosthesis that achieved high accuracy after short training sessions.
  • The neuroprosthesis demonstrated impressive performance, sustaining over 97% accuracy and enabling the participant to speak at a rate of about 32 words per minute for an extended period post-implantation.

Article Abstract

Background: Brain-computer interfaces can enable communication for people with paralysis by transforming cortical activity associated with attempted speech into text on a computer screen. Communication with brain-computer interfaces has been restricted by extensive training requirements and limited accuracy.

Methods: A 45-year-old man with amyotrophic lateral sclerosis (ALS) with tetraparesis and severe dysarthria underwent surgical implantation of four microelectrode arrays into his left ventral precentral gyrus 5 years after the onset of the illness; these arrays recorded neural activity from 256 intracortical electrodes. We report the results of decoding his cortical neural activity as he attempted to speak in both prompted and unstructured conversational contexts. Decoded words were displayed on a screen and then vocalized with the use of text-to-speech software designed to sound like his pre-ALS voice.

Results: On the first day of use (25 days after surgery), the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. Calibration of the neuroprosthesis required 30 minutes of cortical recordings while the participant attempted to speak, followed by subsequent processing. On the second day, after 1.4 additional hours of system training, the neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary. With further training data, the neuroprosthesis sustained 97.5% accuracy over a period of 8.4 months after surgical implantation, and the participant used it to communicate in self-paced conversations at a rate of approximately 32 words per minute for more than 248 cumulative hours.

Conclusions: In a person with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore conversational communication after brief training. (Funded by the Office of the Assistant Secretary of Defense for Health Affairs and others; BrainGate2 ClinicalTrials.gov number, NCT00912041.).

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11328962PMC
http://dx.doi.org/10.1056/NEJMoa2314132DOI Listing

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