Classification of Bio-optical signals using soft computing tools

G. Subramanya Nayak, C. Puttamadappa, Akshata Kamath, B. Raja Sudeep, K. Kavitha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 flittered 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

Original languageEnglish
Title of host publicationProc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications
Pages661-663
Number of pages3
DOIs
Publication statusPublished - 2008
Event9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 in conjunction with 2nd International Workshop on Advanced Internet Technology and Applications, AITA 2008 - Phuket, Thailand
Duration: 06-08-200808-08-2008

Conference

Conference9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 in conjunction with 2nd International Workshop on Advanced Internet Technology and Applications, AITA 2008
CountryThailand
CityPhuket
Period06-08-0808-08-08

Fingerprint

Soft computing
Pathology
Tissue
Backpropagation algorithms
Feedforward neural networks
Power spectral density
Multilayer neural networks
MATLAB
Skin

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

Cite this

Nayak, G. S., Puttamadappa, C., Kamath, A., Sudeep, B. R., & Kavitha, K. (2008). Classification of Bio-optical signals using soft computing tools. In Proc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications (pp. 661-663). [4617448] https://doi.org/10.1109/SNPD.2008.9
Nayak, G. Subramanya ; Puttamadappa, C. ; Kamath, Akshata ; Sudeep, B. Raja ; Kavitha, K. / Classification of Bio-optical signals using soft computing tools. Proc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications. 2008. pp. 661-663
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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 flittered 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",
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Nayak, GS, Puttamadappa, C, Kamath, A, Sudeep, BR & Kavitha, K 2008, Classification of Bio-optical signals using soft computing tools. in Proc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications., 4617448, pp. 661-663, 9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 in conjunction with 2nd International Workshop on Advanced Internet Technology and Applications, AITA 2008, Phuket, Thailand, 06-08-08. https://doi.org/10.1109/SNPD.2008.9

Classification of Bio-optical signals using soft computing tools. / Nayak, G. Subramanya; Puttamadappa, C.; Kamath, Akshata; Sudeep, B. Raja; Kavitha, K.

Proc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications. 2008. p. 661-663 4617448.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Nayak GS, Puttamadappa C, Kamath A, Sudeep BR, Kavitha K. Classification of Bio-optical signals using soft computing tools. In Proc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications. 2008. p. 661-663. 4617448 https://doi.org/10.1109/SNPD.2008.9