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"Imagine being unable to move anything other than your eyes up and down — a system like this might allow you to type your thoughts at speeds comparable to normal handwriting or smartphone typing," he told AFP .The 65-year-old is "typing" at a rate comparable to that of his peers clicking on a mobile, on a computer that might one day help paralyzed people interact quickly and easily.
The researchers combined artificial intelligence (AI) software with a system implanted in the man's brain called a brain-computer interface (BCI). According to the report, the program could decipher information from the machine and translate the man's thoughts regarding handwriting into text on a computer screen.
The man was able to write more than twice as easily using this method as he was using a previous method developed by Stanford researchers, who published their results in the journal eLife in 2017.According to the researchers, the participant was able to write at a rate of approximately 18 words per minute while maintaining 94.1 percent accuracy. On a smartphone, able-bodied people of the same age will type approximately 23 words per minute.
Advantages of a chip:
Each chip in the mind has 100 electrodes that receive neuronal signals from the motor cortex - the outermost region of the brain - that regulates the movement of hands. The experts then sent the neural signals to a computer through wires, where AI algorithms decoded them and deduced T5's intended hand and finger motion.
"This method represents a significant improvement over existing BCIs, which depend on the use of the brain to move a cursor on the screen to 'type' words," stated lead author Frank Willett. "Taking every letter to write, it creates a unique pattern of brain activity that facilitates the computer to identify what is written much more accurately and speedily."
Experts claim more evidence of the method's durability, protection, and effectiveness is needed before it can be used in clinical settings. These techniques, according to the researchers, may be used to decode speech from someone who can no longer communicate, or any other sequential behavior that cannot be observed directly.
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