MACHINE LEARNING TRANSLATES BRAIN SIGNALS FROM A PARALYSED PATIENT

Default Author • September 20, 2021

Researchers are directly harnessing electrical brain activity to help give a voice to those with paralysis and speech impediments.


A recent study was conducted in a single 36-year-old patient with anarthria, a condition that renders people unable to articulate words because they lose control of muscles tied to speech. The researchers implanted an array of electrodes in the patient’s brain, in the area that controls the vocal tracts, known as the sensorimotor cortex.


They measured the electrical activity in the patient’s brain while he was trying to say a word and used a machine learning algorithm to then match brain signals with specific words. With this code, the scientists prompted the patient with sentences and asked him to read them, as though he were trying to say them out loud. The algorithm interpreted what the patient was trying to say with 75% accuracy.


The future of AI and machine learning for medical applications is bright and we’re excited to hear of advancements happening everyday. Contact us to see how you can leverage AI in your organisation.

Tag :- AI, Artificial Intelligence, Machine Learning, Data, Tech

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