An Integrated Approach of CNT Front-end Amplifier towards Spikes Monitoring for Neuro-prosthetic Diagnosis

Abstract

The future neuro-prosthetic devices would be required spikes data monitoring through sub-nanoscale transistors that enables to neuroscientists and clinicals for scalable, wireless and implantable applications. This research investigates the spikes monitoring through integrated CNT front-end amplifier for neuro-prosthetic diagnosis. The proposed carbon nanotube-based architecture consists of front-end amplifier (FEA), integrate fire neuron and pseudo resistor technique that observed high electrical performance through neural activity. A pseudo resistor technique ensures large input impedance for integrated FEA by compensating the input leakage current. While carbon nanotube based FEA provides low-voltage operation with directly impacts on the power consumption and also give detector size that demonstrates fidelity of the neural signals. The observed neural activity shows amplitude of spiking in terms of action potential up to 80 μV while local field potentials up to 40 mV by using proposed architecture. This fully integrated architecture is implemented in Analog cadence virtuoso using design kit of CNT process. The fabricated chip consumes less power consumption of 2 μW under the supply voltage of 0.7 V. The experimental and simulated results of the integrated FEA achieves 60 GΩ of input impedance and input referred noise of 8.5 nv/$\rm\sqrt{Hz}$ over the wide bandwidth. Moreover, measured gain of the amplifier achieves 75 dB midband from range of 1 KHz to 35 KHz. The proposed research provides refreshing neural recording data through nanotube integrated circuit and which could be beneficial for the next generation neuroscientists.