Publications

Borrowing from nature, neural-inspired interception algorithms were implemented onboard a vehicle. To maximize success, work was conducted in parallel within a simulated environment and on physical hardware. The intercept vehicle used only optical imaging to detect and track the target. A successful outcome is the proof-of-concept demonstration of a neural-inspired algorithm autonomously guiding a vehicle to intercept a moving target. This work tried to establish the key parameters for the intercept algorithm (sensors and vehicle) and expand the knowledge and capabilities of implementing neural-inspired algorithms in simulation and on hardware.

While existing work in neural interfaces is largely geared toward the restoration of lost function in amputees or victims of neurological injuries, similar technology may also facilitate augmentation of healthy subjects. One example is the potential to learn a new, unnatural sense through a neural interface. The use of neural interfaces in healthy subjects would require an even greater level of safety and convenience than in disabled subjects, including reliable, robust bidirectional implants with highly-portable components outside the skin. We present our progress to date in the development of a bidirectional neural interface system intended for completely untethered use. The system consists of a wireless stimulating and recording peripheral nerve implant powered by a rechargeable battery, and a wearable package that communicates wirelessly both with the implant and with a computer or a network of independent sensor nodes. Once validated, such a system could permit the exploration of increasingly realistic use of neural interfaces both for restoration and for augmentation. © 2007 IEEE.

Abstract not provided.