Low power microsystems for brain computer interfaces

Abstract

Neural interfaces convert brain signals into outputs that infer brain intentional states. As a communication channel it can be used to implement brain computer interfaces (BCIs) to aid subjects with severe motor disabilities. The realization of this emerging paradigm of neural prosthetics requires extremely low power, small, low noise, highly parallel and distributed signal acquisition hardware platforms with on-chip signal processing and energy efficient wireless data communication. This paper presents a brief overview of the hardware challenges and considerations in BCI systems.