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Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

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A high-performance speech neuroprosthesis.

Francis R Willett, Erin Kunz, Chaofei Fan

Biorxiv : the Preprint Server for Biology

|January 30, 2023

Summary

This summary is machine-generated.

This study introduces a new speech brain-computer interface (BCI) that decodes attempted speech from brain signals. This advanced BCI offers faster, more accurate communication for individuals with paralysis, approaching natural conversation speeds.

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A Protocol for Comprehensive Assessment of Bulbar Dysfunction in Amyotrophic Lateral Sclerosis ALS

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Published on: February 21, 2011

Area of Science:

Neuroscience
Biomedical Engineering
Assistive Technology

Background:

Speech brain-computer interfaces (BCIs) aim to restore communication for individuals with paralysis.
Existing speech BCIs lack the accuracy and speed for unconstrained communication from large vocabularies.

Approach:

Developed a novel speech-to-text BCI utilizing high-resolution intracortical microelectrode array recordings of neural activity.
The BCI decodes spiking activity associated with attempted speech movements.

Key Points:

Achieved a 9.1% word error rate on a 50-word vocabulary and 23.8% on a 125,000-word vocabulary, significantly outperforming prior speech BCIs.
Decoded speech at 62 words per minute, substantially faster than previous BCI records and approaching natural conversation.
Identified key neural code features for speech, including spatially intermixed tuning and persistent articulatory representations, even years after paralysis onset.

Conclusions:

This intracortical speech BCI demonstrates a viable method for restoring rapid communication in individuals unable to speak due to conditions like ALS.
The findings pave the way for more effective assistive communication technologies.