Spike rate estimation using Bayesian Adaptive Kernel Smoother (BAKS) and its application to brain machine interfaces

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Title: Spike rate estimation using Bayesian Adaptive Kernel Smoother (BAKS) and its application to brain machine interfaces
Authors: Ahmadi, N
Constandinou, TG
Bouganis, C
Item Type: Conference Paper
Abstract: Brain Machine Interfaces (BMIs) mostly utilise spike rate as an input feature for decoding a desired motor output as it conveys a useful measure to the underlying neuronal activity. The spike rate is typically estimated by a using non-overlap binning method that yields a coarse estimate. There exist several methods that can produce a smooth estimate which could potentially improve the decoding performance. However, these methods are relatively computationally heavy for real-time BMIs. To address this issue, we propose a new method for estimating spike rate that is able to yield a smooth estimate and also amenable to real-time BMIs. The proposed method, referred to as Bayesian adaptive kernel smoother (BAKS), employs kernel smoothing technique that considers the bandwidth as a random variable with prior distribution which is adaptively updated through a Bayesian framework. With appropriate selection of prior distribution and kernel function, an analytical expression can be achieved for the kernel bandwidth. We apply BAKS and evaluate its impact on of fline BMI decoding performance using Kalman filter. The results show that overlap BAKS improved the decoding performance up to 3.33% and 12.93% compared to overlap and non-overlap binning methods, respectively, depending on the window size. This suggests the feasibility and the potential use of BAKS method for real-time BMIs.
Issue Date: 17-Jul-2018
Date of Acceptance: 7-Apr-2018
URI: http://hdl.handle.net/10044/1/58748
Publisher: IEEE
Copyright Statement: This paper is embargoed until publication.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/M020975/1
Conference Name: 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publication Status: Accepted
Start Date: 2018-07-17
Finish Date: 2018-07-21
Conference Place: Honolulu, Hawaii
Embargo Date: publication subject to indefinite embargo
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



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