@inproceedings{Barsakcioglu:2013,
author = {Barsakcioglu, DY and Eftekhar, A and Constandinou, TG},
title = {Design Optimisation of Front-End Neural Interfaces for Spike Sorting Systems},
url = {http://hdl.handle.net/10044/1/10971},
year = {2013}
}

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TY  - CPAPER
AB  - This work investigates the impact of the analoguefront-end design (pre-amplifier, filter and converter) on spike sorting performance in neural interfaces. By examining key design parameters including the signal-to-noise ratio, bandwidth,filter type/order, data converter resolution and sampling rate, their sensitivity to spike sorting accuracy is assessed. This is applied to commonly used spike sorting methods such as template matching, 2nd derivative-features, and principle component analysis. The results reveal a near optimum set of parameters to increase performance given the hardware-constraints. Finally, the relative costs of these design parameters on resource efficiency (silicon area and power requirements) are quantified through reviewing the state-of-the-art.
AU  - Barsakcioglu,DY
AU  - Eftekhar,A
AU  - Constandinou,TG
PY  - 2013///
TI  - Design Optimisation of Front-End Neural Interfaces for Spike Sorting Systems
UR  - http://hdl.handle.net/10044/1/10971
ER  - 

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