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: gen...

Full description

Saved in:
Bibliographic Details
Published in2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2012; pp. 4579 - 4582
Main Authors Li, W. X. Y., Chan, R. H. M., Dong Song, Berger, T. W., Cheung, R. C. C.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.01.2012
Subjects
Action Potentials
Computational modeling
Diagnosis, Computer-Assisted - instrumentation
Electroencephalography - instrumentation
Equipment Design
Equipment Failure Analysis
Estimation
Field programmable gate arrays
Hardware
Hippocampus - physiopathology
Humans
Nervous System Diseases - diagnosis
Nervous System Diseases - physiopathology
Nervous System Diseases - rehabilitation
Predictive models
Prostheses and Implants
Prosthetics
Signal Processing, Computer-Assisted - instrumentation
Software
Online AccessGet full text

Cover

More Information
Summary: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.
ISBN:1424441196
9781424441198
ISSN:1094-687X
1557-170X
1558-4615
DOI:10.1109/EMBC.2012.6346986