AI and Brain-Computer Interface May Predict Intended Motion in Those With Paralysis

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Article Excerpt:

Artificial intelligence (AI) machine learning combined with brain–computer interface (BCI) neurotechnology is offering a glimmer of hope for the disabled. A new study published in the Journal of Neurophysiology shows how an AI-enabled BCI has the potential to enable those with severe paralysis from spinal cord injury to control external devices by predicting intended movement using a wearable sensor.

“This wearable system has the potential to enable people with tetraplegia to control assistive devices through movement intent,” wrote the researchers affiliated with Carnegie Mellon University, the University of Pittsburgh, Imperial College in London, and the Battelle Memorial Institute in Ohio.

These results demonstrate the potential to create a wearable sensor for determining movement intentions from spared motor neurons, which may enable people with severe tetraplegia to control assistive devices such as computers, wheelchairs, and robotic manipulators,” concluded the scientists.

Analysis:

Artificial Intelligence is up and coming, with its capabilities still being discovered. I still struggle to grasp just how this new technology is able to do things like predicting movements based off of thoughts alone. This technology is essentially a new form communication for those who are unable to communicate, such as individuals with paralysis, amputation, and a host of neurological disorders such as Parkinson’s disease, ALS, and epilepsy. It is combined with BCI (Brain Computer Interface) to help translate the myoelectric activity into commands for moving prosthetic limbs, etc. The wearable interface is far less invasive than other implant methods. This technology seems telepathic in ways, as there is no visual cues given by the user, only ones that are triggered by the thoughts of the user.