Advancing neuromodulation using a dynamic control framework.

The current state of neuromodulation can be cast in a classical dynamic control framework such that the nervous system is the classical "plant", the neural stimulator is the controller, tools to collect clinical data are the sensors, and the physician's judgment is the state estimator. This framework characterizes the types of opportunities available to advance neuromodulation. In particular, technology can potentially address two dominant factors limiting the performance of the control system: "observability," the ability to observe the state of the system from output measurements, and "controllability," the ability to drive the system to a desired state using control actuation.

An implantable bi-directional brain-machine interface system for chronic neuroprosthesis research.

An implantable bi-directional brain-machine interface (BMI) prototype is presented. With sensing, algorithm, wireless telemetry, and stimulation therapy capabilities, the system is designed for chronic studies exploring closed-loop and diagnostic opportunities for neuroprosthetics. In particular, we hope to enable fundamental chronic research into the physiology of neurological disorders, define key electrical biomarkers related to disease, and apply this learning to patient-specific algorithms for therapeutic stimulation and diagnostics.