Development of a closed-loop feedback system for real-time control of a high-dimensional Brain Machine Interface.

As the field of neural prosthetics advances, Brain Machine Interface (BMI) design requires the development of virtual prostheses that allow decoding algorithms to be tested for efficacy in a time- and cost-efficient manner. Using an x-ray and MRI-guided skeletal reconstruction, and a graphic artist's rendering of an anatomically correct macaque upper limb, we created a virtual avatar capable of independent movement across 27 degrees-of-freedom (DOF). Using a custom software interface, we animated the avatar's movements in real-time using kinematic data acquired from awake, behaving macaque subjects using a 16 camera motion capture system. Using this system, we demonstrate real-time, closed-loop control of up to 27 DOFs in a virtual prosthetic device. Thus, we describe a practical method of testing the efficacy of high-complexity BMI decoding algorithms without the expense of fabricating a physical prosthetic.