University of Pittsburgh

West Virginia University

Jennifer Collinger

Sergiy Yakovenko

Matthew Boots

Robert Gaunt

Valeriya Gritsenko

Anton Sobinov

Lee Fisher

Brian Dekleva

Disclosed herein are methods and systems for transient-based decoding of neural signals. In one aspect, a device such as a brain-computer interface (BCI), includes at least one processor configured to receive a plurality of neural signals from a subject. The at least one processor can detect, from the plurality of neural signals, first neural activity unique to a first defined temporal window corresponding to an onset phase of an intended action of the subject. The at least one processor can detect, from the plurality of neural signals, second neural activity unique to a second defined temporal window, occurring after the first temporal window and corresponding to an offset phase of the intended action. The at least one processor can generate at least one output indicative of the intended action, responsive to detecting at least one of the first neural activity or the second neural activity.

Systems and methods of transient-based decoding of neural signals

A system and method for controlling a device, such as a virtual reality (VR) and/or a prosthetic limb are provided. A biomimetic controller of the system comprises a signal processor and a musculoskeletal model. The signal processor processes M biological signals received from a residual limb to transform the M biological signals into N activation signals, where M and N are integers and M is less than N. The musculoskeletal model transforms the N activation signals into intended motion signals. A prosthesis controller transforms the intended motion signals into three or more control signals that are outputted from an output port of the prosthesis controller. A controlled device receives the control signals and performs one or more tasks in accordance with the control signals.

Systems and methods for approximating musculoskeletal dynamics

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Pittsburgh, PA, United States of America

Jennifer Collinger