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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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International Journal of Computer Technology and Applications
2011
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| Subjects: | |
| Online Access: | http://eprints.utm.my/6965/2/ijcta2011020120.pdf |
| _version_ | 1825909975584604160 |
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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. |
| collection | ePrints |
| 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. |
| first_indexed | 2024-03-05T18:10:09Z |
| format | Article |
| id | utm.eprints-6965 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T18:10:09Z |
| publishDate | 2011 |
| publisher | International Journal of Computer Technology and Applications |
| record_format | dspace |
| spelling | 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
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| title_full | Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
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| title_fullStr | Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
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| title_full_unstemmed | Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
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| title_short | Application of bioelectrical impedance sensing techniques for dengue infection with non-linear autoregressive model
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| 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 |
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