Wednesday 22 May 2019

'Mind-reading' brain implants let patients speak

The brain implant could allow those with a disability to speak at the speed of normal speech. (stock photo)
The brain implant could allow those with a disability to speak at the speed of normal speech. (stock photo)

Sarah Knapton London

A "mind-reading" brain implant that decodes what a person is trying to say and plays it back through a computer could help stroke victims to speak again.

Many diseases leave patients unable to control the muscles that form words, but researchers realised those muscles are still sending messages to the brain when a paralysed person tries to speak.

A team at the University of California San Francisco (UCSF) worked out which pulses from the larynx, lips, jaw and tongue corresponded to which sounds.

They then used a computer to recreate the vocal tract and when they sent the brain signals to the virtual muscles, they formed words, generating natural sounding synthetic speech - although they admit that abrupt sounds like Bs and Ps are still "a bit fuzzy".

The breakthrough offers hope for people suffering from stroke, brain injury, or neurodegenerative illness such as Parkinson's, multiple sclerosis and amyotrophic lateral sclerosis, the condition that killed Professor Stephen Hawking.

Before his death last year, Prof Hawking had to "speak" letter-by-letter using an infrared sensor on his glasses, at around 10 words per minute.

The new device could allow those with a disability to speak at the speed of normal speech.

"This study demonstrates that we can generate entire spoken sentences based on an individual's brain activity," said Edward Chang, professor of neurological surgery at UCSF.

Previous attempts to turn thoughts into synthesised speech have faltered because the brain regions that control speech do not represent sounds, but the instructions needed to co-ordinate the movements of the vocal tract.

The researchers realised that a virtual vocal tract was necessary to translate the signals.

Irish Independent

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