Imperial College London
Alternate

DrDeren YusufBarsakcioglu

Faculty of Engineering, Department of Bioengineering

Research Associate
 
 
 
//

Contact

 

deren.barsakcioglu10

 
 
//

Location

 

U421Sir Michael Uren HubWhite City Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Paraskevopoulou:2013:10.1016/j.jneumeth.2013.01.012,
author = {Paraskevopoulou, SE and Barsakcioglu, D and Saberi, M and Eftekhar, A and Constandinou, TG},
doi = {10.1016/j.jneumeth.2013.01.012},
journal = {Journal of Neuroscience Methods},
pages = {29--37},
title = {Feature Extraction using First and Second Derivative Extrema (FSDE), for Real-time and Hardware-Efficient Spike Sorting},
url = {http://dx.doi.org/10.1016/j.jneumeth.2013.01.012},
volume = {215},
year = {2013}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Next generation neural interfaces aspire to achieve real-time multi-channel systems by integrating spike sorting on chip to overcome limitations in communication channel capacity. The feasibility of this approach relies on developing highly-efficient algorithms for feature extraction and clustering with the potential of low-power hardware implementation. We are proposing a feature extraction method, not requiring any calibration, based on first and second derivative features of the spike waveform. The accuracy and  computational complexity of the proposed method are quantified and compared against commonly used feature extraction methods, through simulation across four datasets (with different single units) at multiple noise levels (ranging from 5 to 20% of the signal amplitude). The average classification error is shown to be below 7% with a computational complexity of 2N-3, where N is the number of sample points of each spike. Overall, this method presents a good trade-off between accuracy and computational complexity and is thus particularly well-suited for hardware-efficient implementation.
AU  - Paraskevopoulou,SE
AU  - Barsakcioglu,D
AU  - Saberi,M
AU  - Eftekhar,A
AU  - Constandinou,TG
DO  - 10.1016/j.jneumeth.2013.01.012
EP  - 37
PY  - 2013///
SN  - 0165-0270
SP  - 29
TI  - Feature Extraction using First and Second Derivative Extrema (FSDE), for Real-time and Hardware-Efficient Spike Sorting
T2  - Journal of Neuroscience Methods
UR  - http://dx.doi.org/10.1016/j.jneumeth.2013.01.012
UR  - http://hdl.handle.net/10044/1/10996
VL  - 215
ER  -
Download