Awarded in 2015
Home Department: Electrical Engineering
Faculty Advisors: Krishna Shenoy (Electrical Engineering) and Kwabena Boahen (Bioengineering)
Research Title: Neural control of a robotic arm using an adaptive brain-machine interface enabled by error detection feedback
Research Description: Brain machine interfaces (BMIs) aim to improve communication ability for people with paralysis (such as via cortical control of a computer cursor). Currently, invasive BMIs are hampered by low performance. However, a BMI user has constant visual feedback about the ongoing task and any errors could potentially be reflected in his brain activity. Nir’s goal is to characterize the neural activity correlated with those errors, and to incorporate them as feedback to the BMI decoder. In his preliminary experiments with monkeys, Nir utilized those signals to auto-delete failures. He will further develop these approaches to create a more natural and accurate BMI, capable of robotic-arm control.