All ETDs from UAB

Advisory Committee Chair

Mohammad R Haider

Advisory Committee Members

Karthikeyan Lingasubramanian

Dalton S Nelson

Document Type


Date of Award


Degree Name by School

Master of Electrical Engineering (MEE) School of Engineering


With the advances in the integrated circuit technologies, various types of micro- and nano-sensors are increasingly being utilized in different fields such as medical monitoring, wireless health monitoring, structural health monitoring, where low power consumption, small dimensions, multi-signal sensing capabilities and wireless telemetry are required. Various types of bio-electrical signals are used in the medical sensor systems for diagnostics as well as therapeutic interventions. Usually, bio-signals have the common features of low frequency, and low amplitude level. In this work, a low current sensor signal monitoring system has been proposed and developed, which possesses several merits in terms of high system sensitivity, low power dissipation, and high linearity. The proposed system comprises of mainly three stages: a frequency generation stage with sensor current detection, a sampling window generation stage and a data converting stage. By employing multiple low-power design techniques and models, an oscillator based frequency generation stage has been developed. The window generation system comprises of a D flip-flop, an AND gate and a high-frequency clock signal. A binary counter has been used for data conversion. For the oscillator frequency generation stage, two neuron model based system has been implemented, the first one is using Izhikevich neuron model, and the other one is using Hodgkin-Huxley model. Hodgkin-Huxley model has been implemented with CMOS based architecture which is designed with a standard 130-nm CMOS process. Because of low input dynamic range of neuron based architecture, a ring oscillator based architecture has also been developed for sensor signal monitoring system with the cost of high power consumption. A low airflow detection system has been demonstrated using the ring oscillator based system. The total power dissipation of the neuron-inspired system is 323 nW with 1 V power supply and that of the ring oscillator based system is 22.6 µW with 800 mV.

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