A dual mode FPGA design for the hippocampal prosthesis.
One important step towards the cognitive neural prosthesis design is to achieve real-time prediction of neuronal firing pattern. An FPGA-based hardware computational platform is designed to guarantee this hard real-time signal processing requirement. The proposed platform can work in dual modes: generalized Laguerre-Volterra model parameters estimation and output prediction, and can switch between these two important system functions. Compared with the traditional software-based platform implemented in C, the hardware platform achieves better efficiency in doing the biocomputations by up to thousandfold speedup in this process.
Department of Electrical Engineering, City University of Hong Kong, Hong Kong. xyli@ee.cityu.edu.hk
Will X Y
WX
Li
Rosa H M
RH
Chan
Dong
D
Song
Theodore W
TW
Berger
Ray C C
RC
Cheung
D000200:Action Potentials; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D004569:Electroencephalography / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006624:Hippocampus / Q000503:physiopathology*; D006801:Humans; D009422:Nervous System Diseases / Q000175:diagnosis* / Q000503:physiopathology* / Q000534:rehabilitation; D019736:Prostheses and Implants; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*