A Neuron Model Based Ultralow Current Sensor System for Bioapplications

Abstract

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.

An Oscillatory Neural Network Based Local Processing Unit for Pattern Recognition Applications

“…Technological innovations of sensors and integrated circuit technology have resulted in wireless sensing for various applications [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. The massive scale of sensor data from an infrastructure creates a burden to the property owner to process and extract meaningful information.…”