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Numerical Simulation of Nanoscale Finfet Photodetector for Optimal Detection of Biological Signals Using Interpolating Wavelets
Progress In Electromagnetics Research B, Vol. 31, 239-260, 2011
The biosensor design for sensing of biological signals is highly complex for accurate detection. Optimal detection of biological signals is necessary for distinguishing different tissues. This paper proposes a threshold-based detection technique which provides significant improvement in FinFET optical biosensor performance using wavelet coefficients. It uses a simple maximum likelihood (ML) function for detecting the threshold values. In this method, we have considered the different layers of body tissue as a turbid medium. To the best of our knowledge, this method is the first of its kind for classifying different tissues using threshold value of optical signals obtained from the surface potential variations of nanoscale FinFET illuminated by laser source of different wavelengths. By using this method, the point to point variations in tissue composition and structural variations in healthy and diseased tissues could be identified. The results obtained are used to examine the performance of the device for its suitable use as a nanoscale sensor.
R. Ramesh, M. Madheswaran, and K. Kannan, "Numerical Simulation of Nanoscale Finfet Photodetector for Optimal Detection of Biological Signals Using Interpolating Wavelets," Progress In Electromagnetics Research B, Vol. 31, 239-260, 2011.

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