Imperial College London
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Professor Timothy Constandinou

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Bioelectronics
 
 
 
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Contact

 

+44 (0)20 7594 0790t.constandinou Website

 
 
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Assistant

 

Miss Izabela Wojcicka-Grzesiak +44 (0)20 7594 0701

 
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Location

 

B407Bessemer BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Zhang:2022:10.1109/EMBC48229.2022.9871955,
author = {Zhang, Z and Constandinou, TG},
doi = {10.1109/EMBC48229.2022.9871955},
journal = {Annu Int Conf IEEE Eng Med Biol Soc},
pages = {2328--2331},
title = {Selecting an effective amplitude threshold for neural spike detection.},
url = {http://dx.doi.org/10.1109/EMBC48229.2022.9871955},
volume = {2022},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper assesses and challenges whether commonly used methods for defining amplitude thresholds for spike detection are optimal. This is achieved through empirical testing of single amplitude thresholds across multiple recordings of varying SNR levels. Our results suggest that the most widely used noise-statistics-driven threshold can suffer from parameter deviation in different noise levels. The spike-noise-driven threshold can be an ideal approach to set the threshold for spike detection, which suffers less from the parameter deviation and is robust to sub-optimal settings.
AU  - Zhang,Z
AU  - Constandinou,TG
DO  - 10.1109/EMBC48229.2022.9871955
EP  - 2331
PY  - 2022///
SP  - 2328
TI  - Selecting an effective amplitude threshold for neural spike detection.
T2  - Annu Int Conf IEEE Eng Med Biol Soc
UR  - http://dx.doi.org/10.1109/EMBC48229.2022.9871955
UR  - https://www.ncbi.nlm.nih.gov/pubmed/36085877
VL  - 2022
ER  -
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