Brain-Machine Interface Utilizing Interventions to Emphasize Aspects of Neural Variance and Decode Speed and Angle
AssigneeThe Board of Trustees of the Leland Stanford Junior University
InventorsJonathan C. Kao, Chethan Pandarinath, Paul Nuyujukian, Krishna V. Shenoy
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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.
Claims3
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.
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.
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.
Dependencies are inferred from the claim text.