Brain-Machine Interface Utilizing Interventions to Emphasize Aspects of Neural Variance and Decode Speed and Angle

Abstract

A brain machine interface (BMI) for restoring performance of poorly performing decoders is provided. The BMI has a decoder for decoding neural signals for controlling the brain machine interface. The decoder separates in part neural signals associated with a direction of movement and neural signals associated with a speed of movement of the brain machine interface. The decoder assigns relatively greater weight to the neural signals associated with a direction of movement.

What is claimed is: 
     
         1 . A brain machine interface, comprising:
 (a) an algorithm executable by a computer for separating neural signals into: (i) neural signals related to a speed of a prosthetic device and (ii) neural signals related to an angle of movement of the prosthetic device; and   b) a decoder algorithm executable by the computer for mapping the speed-related neural signals and mapping the angle-related neural signals to a kinematic space or the prosthetic device.   
     
     
         2 . A brain machine interface, comprising a decoder algorithm executable by a computer for regressing neural signals against an angle and magnitude of a velocity and outputting to a kinematic space or a prosthetic device such that the dimensions of the output kinematic space or the prosthetic device are independently and separately estimated and not derived by a combination of the output of the decoder algorithm. 
     
     
         3 . A brain machine interface, comprising a decoder algorithm executable by a computer for incorporating previously known information regarding neural signals that are no longer present due to the loss of neural recording, neuron cell death, or noise.