Classification of Bio-optical Signals using Soft Computing Tools

Nayak, Subramanya G and Puttamadappa, C and Kamath, Akshata and Sudeep, Raja B and Kavitha, K (2008) Classification of Bio-optical Signals using Soft Computing Tools. In: Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 6-8 Aug. 2008 .

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Abstract

The identification of the state of human skin tissues is discussed here. The Bio-optical signals recorded in vitro have been analyzed by extracting various statistical features. Using LAB VIEW 7.1 programs/tools, different statistical features are extracted from both normal and pathology spectra. Each spectrum is filttered and normalized. Then different features like Skewness, summation, median residuals, power spectral density, etc were extracted. The values of the feature vector reveal information regarding tissue state. The values of the feature vector reveal information regarding tissue state. These parameters have been analyzed for discrimination between normal and pathology conditions. For analysis, a specific data set has been considered. Further discrimination between normal and pathology spectra is also be achieved by using MATLAB @6.1 tool based classical multilayer feed forward neural network with back propagation algorithm

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Artificial Neural network, Principal Component Analysis, Back Propagation Algorithm
Subjects: Engineering > MIT Manipal > Electronics and Communication
Depositing User: MIT Library
Date Deposited: 02 Aug 2011 04:19
Last Modified: 02 Aug 2011 04:19
URI: http://eprints.manipal.edu/id/eprint/1109

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