Millions of people worldwide suffer from diseases that lead to paralysis through disruption of signal pathways between the brain and the muscles. Neuroprosthetic devices are designed to restore lost function and could be used to form an electronic ‘neural bypass’ to circumvent disconnected pathways in the nervous system. It has previously been shown that intracortically recorded signals can be decoded to extract information related to motion, allowing non-human primates and paralysed humans to control computers and robotic arms through imagined movements. In non-human primates, these types of signal have also been used to drive activation of chemically paralysed arm muscles. Here we show that intracortically recorded signals can be linked in real-time to muscle activation to restore movement in a paralysed human. We used a chronically implanted intracortical microelectrode array to record multiunit activity from the motor cortex in a study participant with quadriplegia from cervical spinal cord injury. We applied machine-learning algorithms to decode the neuronal activity and control activation of the participant’s forearm muscles through a custom-built high-resolution neuromuscular electrical stimulation system. The system provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and hand motions. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Clinical assessment showed that, when using the system, his motor impairment improved from the fifth to the sixth cervical (C5-C6) to the seventh cervical to first thoracic (C7-T1) level unilaterally, conferring on him the critical abilities to grasp, manipulate, and release objects. This is the first demonstration to our knowledge of successful control of muscle activation using intracortically recorded signals in a paralysed human. These results have significant implications in advancing neuroprosthetic technology for people worldwide living with the effects of paralysis.
a, Red regions are brain areas active during attempts to mimic hand movements
b Neuromuscular electrical stimulation sleeve
We don’t often report on non-MS related stuff but thought this report is really worth a post
The study participant was a 24-year-old male with stable, non-spastic C5/C6 quadriplegia from cervical spinal cord injury (SCI) sustained in a diving accident 4 years previously.
The researchers took fMRI (functional magnetic resonance imaging) scans of the guy’s brain while he tried to mirror videos of hand movements. This identified a precise area of the motor cortex — the area of the brain that controls movement — linked to these movements. Surgery was then performed to implant a flexible chip that detects the pattern of electrical activity arising when the participant thinks about moving his hand, and relays it through a cable to a computer. Machine-learning algorithms then translate the signal into electrical messages, which are transmitted to a flexible sleeve that wraps around the participant’s right forearm and stimulates his muscles.He underwent implantation of a Utah microelectrode array in his left primary motor cortex.
The participant attended up to three sessions weekly for 15 months after implantation to use the neural bypass system (NBS).. In each session, he was trained to utilize his motor cortical neuronal activity to control a custom-built high-resolution neuromuscular electrical stimulator (NMES). The NMES delivered electrical stimulation to his paralysed right forearm muscles using an array of 130 electrodes embedded in a custom-made flexible sleeve wrapped around the arm
c. NBS in use with the participant in front a computer monitor.
Amazing technology and a step in the right direct is regaining function to limbs that have lost nervous control. However success in MS will be more difficult than with spinal injury because unless the disease is under control the brain areas controlling the movement may change