{"id":20776,"date":"2023-04-26T07:19:56","date_gmt":"2023-04-26T07:19:56","guid":{"rendered":"http:\/\/localhost\/git\/blackrock\/?post_type=application-story&p=20776"},"modified":"2023-05-12T19:10:36","modified_gmt":"2023-05-12T19:10:36","slug":"human-bci-research-story-neuroprosthesis-speech","status":"publish","type":"application-story","link":"https:\/\/blackrockneurotech.com\/story\/human-bci-research-story-neuroprosthesis-speech\/","title":{"rendered":"Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria"},"content":{"rendered":"\n
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\n Human BCI Research <\/p>\n

\n Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria <\/h1>\n
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\n Results <\/h2>\n
\n “We decoded sentences from the participant\u2019s cortical activity in real time at a median rate of 15.2 words per minute, with a median word error rate of 25.6%. In post hoc analyses, we detected 98% of the attempts by the participant to produce individual words, and we classified words with 47.1% accuracy using cortical signals that were stable throughout the 81-week study period.” (From Abstract – Moses, et al., 2021) <\/div>\n <\/div>\n
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\n Conclusions <\/h3>\n
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“In a person with anarthria and spastic quadriparesis caused by a brain-stem stroke, words and sentences were decoded directly from cortical activity during attempted speech with the use of deep-learning models and a natural-language model.” (From Abstract – Moses, et al., 2021)<\/p>\n

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