Scientists from Johns Hopkins University (JHU) successfully tested a brain-computer neural interface on a paralyzed man. The treatment allowed the patient to control electronic devices at home, including lights and the YouTube app. The research was published in the journal Advanced Science.
In 2014, Tim Evans was diagnosed with amyotrophic lateral sclerosis (ALS), a progressive nervous system disease that causes muscle weakness, paralysis, loss of speech and the ability to swallow. In a new study, researchers reported surgical implantation of a CortiCom device in a man in areas of the brain associated with speech and upper extremity function. The device consists of two electrocorticographic (ECoG) grids of thin, postage-stamp-sized sheets with electrode sensors to record electrical signals generated by thousands of brain cells.
A special algorithm has been developed to convert electrical signals coming from the speech centers of the human brain into computer commands. The 62-year-old can now freely and reliably use six basic commands (up, down, left, right, home and back) to navigate through options. This allows him to control the lighting in the room and the YouTube app. The algorithm was 90% accurate over the three-month study period, with no need for retraining or recalibration.
The study authors explained that the lack of need to retrain the BCI algorithm means that this approach will allow patients to freely use the neural interface whenever and wherever they want, without the need for constant intervention from the researcher.
“We hope that in the future, a patient with severe paralysis will be able to start the day by turning on the lights and watching the news on television, using only signals from his brain,” the scientists said.
Former biotechnologists developed Molecular scaffolding for the treatment of spinal cord injury.