Last year at HIMSS, we introduced a neural bypass system used data from a cortical implant in a paralyzed human to decode imagined movements, bypass the damaged spinal cord injury and stimulate muscles in real time using a neuromuscular electrical stimulation. This year we will show the incredible progress this technology has made including allowing a paralyzed man to complete complex functions tasks relevant to daily living as well as playing a guitar video game and discuss how the system utilizes big data techniques to process the nearly three million data points the system generates every second and how our framework builds custom models tailored for the individual.
Describe a system for bypassing a damaged spinal cord by using large amounts of data collected from a cortical implant to control a muscle stimulation system which moves a paralyzed limb controlled by the subject's thoughts
Examine an example of using big data to create a model that is personalized for individuals to interpret intracortically recorded brain data and translate it into movement
Discuss the potential and some of the pitfalls of using big data to inform a brain computer interface and how these lessons can be applied more broadly