A Neuron Model Based Ultralow Current Sensor System for Bioapplications
Joint Authors
Arifuzzman, A. K. M.
Islam, Mohammad Shafquatul
Haider, M. R.
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-02-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
An ultralow current sensor system based on the Izhikevich neuron model is presented in this paper.
The Izhikevich neuron model has been used for its superior computational efficiency and greater biological plausibility over other well-known neuron spiking models.
Of the many biological neuron spiking features, regular spiking, chattering, and neostriatal spiny projection spiking have been reproduced by adjusting the parameters associated with the model at hand.
This paper also presents a modified interpretation of the regular spiking feature in which the firing pattern is similar to that of the regular spiking but with improved dynamic range offering.
The sensor current ranges between 2 pA and 8 nA and exhibits linearity in the range of 0.9665 to 0.9989 for different spiking features.
The efficacy of the sensor system in detecting low amount of current along with its high linearity attribute makes it very suitable for biomedical applications.
American Psychological Association (APA)
Arifuzzman, A. K. M.& Islam, Mohammad Shafquatul& Haider, M. R.. 2016. A Neuron Model Based Ultralow Current Sensor System for Bioapplications. Journal of Sensors،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1110704
Modern Language Association (MLA)
Arifuzzman, A. K. M.…[et al.]. A Neuron Model Based Ultralow Current Sensor System for Bioapplications. Journal of Sensors No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1110704
American Medical Association (AMA)
Arifuzzman, A. K. M.& Islam, Mohammad Shafquatul& Haider, M. R.. A Neuron Model Based Ultralow Current Sensor System for Bioapplications. Journal of Sensors. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1110704
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110704