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Research Areas

Sub-Nyquist Sampling of Biological Signals

Feedback-Optimized Brain-Machine Interfaces

State-Space Design for Neural Prosthetic Devices




Sub-Nyquist Sampling of Biological Signals

Resource-constrained sampling strategies will unlock greater bandwidth, field-of-view, and battery life for biosignal acquisition hardware. We exploit the parametric description of pulse-like biological signals to explore this opportunity for cardiac and spiking neural activity.

Further Reading: 1 2 3 4

 

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Feedback-Optimized Brain-Machine Interfaces

Feedback is an important concept in a variety of engineering systems. In this research area, we attempt to improve brain-driven devices by describing human-machine interaction in control-theoretic terms that exploits the brain's own response to cognitive and sensory feedback.

Further Reading: 1 2 3

 

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State-Space Design for Brain-Machine Interfaces

Can Bayesian estimation inspire algorithms to restore movement for patients with paralysis and amputation? In this research area, we explore probabilistic models of the patient's intended movement as the basis for decoding a stream of noisy neural signals.

Further Reading: 1 2 3 4 5

 

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