Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model

This paper discussed novel system identification for bioelectrical impedance measurement parameter for monitoring dengue infections by using nonlinear AR (NAR) based on Artificial Neural Network (ANN). Bioelectrical impedance measurement indicate the volume of Hb of the subjects and NAR model w...

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Main Authors: Abdul Rahim, H., Ibrahim, F., Taib, M. N.
Format: Article
Language:en
Published: International Journal of Computer Technology and Applications 2011
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Online Access:http://eprints.utm.my/6965/2/ijcta2011020120.pdf
http://eprints.utm.my/6965/
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author Abdul Rahim, H.
Ibrahim, F.
Taib, M. N.
author_facet Abdul Rahim, H.
Ibrahim, F.
Taib, M. N.
author_sort Abdul Rahim, H.
building UTM Library
collection Institutional Repository
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
continent Asia
country Malaysia
description This paper discussed novel system identification for bioelectrical impedance measurement parameter for monitoring dengue infections by using nonlinear AR (NAR) based on Artificial Neural Network (ANN). Bioelectrical impedance measurement indicate the volume of Hb of the subjects and NAR model with regularized approach yields better accuracy by 80.60% for bioelectrical impedance sensing method. In building the model, three parameter were considered; the final prediction error (FPE), Akaike’s Information Criteria (AIC), and Lipschitz number.
format Article
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institution Universiti Teknologi Malaysia
language en
publishDate 2011
publisher International Journal of Computer Technology and Applications
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spelling my.utm.eprints-69652017-02-15T00:30:10Z http://eprints.utm.my/6965/ Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model Abdul Rahim, H. Ibrahim, F. Taib, M. N. TK Electrical engineering. Electronics Nuclear engineering This paper discussed novel system identification for bioelectrical impedance measurement parameter for monitoring dengue infections by using nonlinear AR (NAR) based on Artificial Neural Network (ANN). Bioelectrical impedance measurement indicate the volume of Hb of the subjects and NAR model with regularized approach yields better accuracy by 80.60% for bioelectrical impedance sensing method. In building the model, three parameter were considered; the final prediction error (FPE), Akaike’s Information Criteria (AIC), and Lipschitz number. International Journal of Computer Technology and Applications 2011 Article PeerReviewed text/html en http://eprints.utm.my/6965/2/ijcta2011020120.pdf Abdul Rahim, H. and Ibrahim, F. and Taib, M. N. (2011) Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model. International Journal of Computer Technology and Applications, 2 (1). pp. 207-215. ISSN 22296093
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Abdul Rahim, H.
Ibrahim, F.
Taib, M. N.
Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
title Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
title_full Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
title_fullStr Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
title_full_unstemmed Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
title_short Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
title_sort application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
topic TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utm.my/6965/2/ijcta2011020120.pdf
http://eprints.utm.my/6965/
url_provider http://eprints.utm.my/