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Brain-Computer Interfaces for Speech Communication.

Jonathan S Brumberg1, Alfonso Nieto-Castanon, Philip R Kennedy

  • 1Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA, 02215, Telephone: (617) 353- 9481, Fax Number: (617) 353-7755.

Speech Communication
|March 6, 2010
PubMed
Summary
This summary is machine-generated.

A novel brain-computer interface (BCI) decodes intended speech directly from brain activity, offering faster silent communication for paralyzed individuals. This intracortical microelectrode approach shows promise for a speech prosthesis.

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Assessment and Communication for People with Disorders of Consciousness
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07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Speech Communication

Background:

  • Current silent speech methods (EMG, EEG) are slow and require constant attention.
  • Electromyography (EMG) is ineffective for individuals with severe paralysis like tetraplegia.
  • Existing brain-computer interfaces (BCIs) for communication are limited in speed and usability.

Purpose of the Study:

  • To develop a faster silent speech communication method for individuals with severe paralysis.
  • To investigate the efficacy of an intracortical microelectrode BCI for predicting intended speech.
  • To assess the long-term viability of neural recording for a speech prosthesis.

Main Methods:

  • Utilized an intracortical microelectrode brain-computer interface (BCI) to record neural activity from speech production areas.
  • Employed neural decoding techniques to predict intended speech information from neuronal signals.
  • Synthesized predicted speech with real-time acoustic feedback (delay < 50 ms).
  • Demonstrated the long-term recording capability (>4 years) of the Neurotrophic Electrode.

Main Results:

  • The BCI successfully predicted intended speech information directly from neural activity.
  • Acoustic feedback facilitated improved user control over an artificial speech synthesizer.
  • User demonstrated enhanced control within and across recording sessions.
  • The Neurotrophic Electrode provided stable, useful neural recordings over an extended period.

Conclusions:

  • An intracortical microelectrode BCI is a viable approach for rapid silent speech communication.
  • This technology holds significant potential as a speech prosthesis for severely paralyzed individuals.
  • The system enables faster communication rates compared to existing assistive technologies.