Neuromorphic computation promises to be an energy-efficient information processing technique both for the biological and the real-world environments. In this paper a novel structure of silicon neuron has been designed for measuring the variation of a sensor capacitance. The current-reuse technique and the subthreshold region operation of MOSFETs help achieving ultra-low-power consumption. The proposed silicon neuron is designed and simulated in 0.13-μm standard CMOS technology. The entire unit consists of 43 transistors and consumes only 33 nW with a supply voltage of 1 V. The output frequency is proportional to the variation of the sensor capacitance.

The proposed silicon neuron for capacitive sensing in biosensors consumes only 33 nW, making it an energy-efficient information processing technique for biological and real-world environments.

Low-power spike-mode silicon neuron for capacitive sensing of a biosensor

Key Takeaway: The proposed silicon neuron for capacitive sensing in biosensors consumes only 33 nW, making it an energy-efficient information processing technique for biological and real-world environments.