A Neuron Model Based Ultralow Current Sensor System for Bioapplications

Joint Authors

Arifuzzman, A. K. M.
Islam, Mohammad Shafquatul
Haider, M. R.

Source

Journal of Sensors

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

Civil Engineering

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