Increased Sensitivity of Biosensors using Evolutionary Algorithm for Bio-Medical Applications

Abstract

The use of bio-medical applications and bio-inspired computing facilitates the diagnosis of human health. The main work of bio-medical applications relies mostly over the biosensors. Biosensor construction are based on piezoelectric, chemical, optical or electronic principles. Field Effect Transistor (FET) based biosensors gain popularity because of some distinct advantages like compact, fast measurement and portable instrumentation. Due to their small size, FET based biosensors are considered as potential candidates for point of care testing. In this paper, we have investigated the sensitivity of FET biosensors based on Evolutionary Algorithm for Bio-Medical (EABM) applications. We have also discussed major limitations in FET based biosensors like inability to detect neutral charged biomolecules and lesser sensitivity. Current mechanism in tunnel FET is based on band to band tunneling and this property is explored to enhance sensitivity of the device. In this paper, sensing is modeled with drain current, while as effect of variation in biomolecule concentration is based on changes in doping concentration and use high dielectric constant materials. The proposed EABM algorithm shows that the optimized value of drain current (sensitivity) is obtained with increase in doping concentrations or dielectric constant at the gate. The results also depict that the proposed EABM approach outperforms existing FET models.