Florida International University

Mohamed Abdelghani

Ranu Jung

James Abbas

Kenneth Horch

Kang K Yen

Arman Sargolzaei

Saman Sargolzaei

Computational models and methods and systems of using the model to estimate variable time delay in the sensorimotor system of a subject are provided. The computational model can estimate variable time delays in the sensorimotor system, predict sensory states based on delayed sensory feedback, and/or control the system in real time. The subject can be a human or a primate. Simulation experiments can show how the model can explain a sensorimotor system's ability to compensate for delays during online learning and control.

Simulation and diagnostic tool for sensorimotor diseases

To ameliorate the detrimental effects of time delays, techniques and systems are disclosed for detecting time delays in a plant, facility, or environment (such as a power system) controlled by an NCS, and for providing more resilient control capabilities for adapting to the detected time delays. A time delay estimate can be determined by comparing the expected state of the plant, calculated from a plant model, with the state of the plant described by its telemetry data. Techniques for adapting to a time delay include: switching to an emergency controller and acting in accordance with a local reference model; sending adjusted control commands in accordance with an expected plant state; and instructing a transmitter to transmit subsequent communications packets over multiple redundant communication channels.

Detection of and responses to time delays in networked control systems

Systems and methods for decoding neural and/or electromyographic signals are provided. A system can include at least one single channel decoder. Optionally, the system can include a demixer in operable communication with the single channel decoders. Each single channel decoder can include a filter to attenuate noise and sharpen spikes in the neural and/or electromyographic signals, a detection function to identify spikes, and a demodulator to get a real-time estimate of motor intent.

Systems and methods for decoding intended motor commands from recorded neural signals for the control of external devices or to interact in virtual environments

Systems and methods to simulate activity that would be recorded using an interface to nerve fibers are provided. Signals, such as motor intent signals, can be converted to neural recordings, such as neural recordings by longitudinal intrafascicular electrodes (LIFEs). Spinal cord motor pools and neural interfaces can be jointly simulated. Realistic simulated neural recordings, such as from electrodes such as LIFEs, can be provided and can be used for the evaluation of decoding algorithms. Systems and methods described herein provide a framework for developing neural interface devices.

Growing community of inventors

Greenville, SC, United States of America

Mohamed Abdelghani