Monitoring haemoglobin status in dengue patients using ARMAX model

Abdul Rahim, H. and Ibrahim, F. and Taib, M.N. and Abdul Rahim, R. and Mad Sam, Y. (2008) Monitoring haemoglobin status in dengue patients using ARMAX model. In: International Symposium on Information Technology 2008, ITSim, 2008, Kuala Lumpur.

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This paper describes the development of linear autoregressive moving average with exogenous input (ARMAX) models to monitor the progression of dengue infection based on hemoglobin status. Three differents ARMAX model order selection criteria namely Final Prediction Error (FPE), Akaike's Information Criteria (AIC) and Lipschitz number have been evaluated and analyzed. The results showed that Lipschitz number has better accuracy compared to FPE and AIC. Finally based on Lipschitz number, appropriate model orders have been selected to monitor the progression of dengue patients based on hemoglobin status. Further work is to apply this appropriate model orders to nonlinear Autoregressive (NARMAX) model. © 2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Conference code: 74115 Export Date: 29 January 2014 Source: Scopus Art. No.: 4631563 doi: 10.1109/ITSIM.2008.4631563 Language of Original Document: English Correspondence Address: Abdul Rahim, H.; Department of Control and Instrumentation Engineering, Faculty of Electrical Engineering, Universiti Teknologi Udai, Johor, Malaysia; email: References: Bethell, D.B., Gamble, J., Loc, P.P., Dung, N.M., Chau, T.T.H., Loan, H.T., Thuy, T.T., Day, N.P.J., Noninvasive measurement of microvascular leakage in patients with dengue hemorhhagic fever (2001) Clin. Infect. Dis, 32, pp. 243-253; Ibrahim, F., Taib, M.N., Sulaiman, S., Wan Abas, W.A.B., Dengue fever (DF) and dengue hemorrhagic fever (DHF) symptoms analysis fron an expert system perspective (2001) Proc. Proc. of 5th IEEE Int. Multi-Topic, pp. 212-215; W. H. Organization, Dengue Haemorrhagic fever Diagnosis, treatment, Prevention, and control, 2nd ed. Geneva: WHO, 1997Ibrahim, F., Taib, M.N., Wan Abas, W.A.B., Chan, C.G., Sulaiman, S., A Novel Approach to Classify Risk in Dengue Hemorrhagic fever (DHF) using Bioelectrical Impedance Analysis (2005) IEEE Trans. Instrum. Meas, 54 (1), pp. 237-244; Ibrahim, F., Ismail, N.A., Taib, M.N., Wan Abas, W.A.B., Modeling of hemoglobin in dengue fever and dengue hemorrhagic fever using biolectrical impedance (2004) Physiol. Meas, 25, pp. 607-615; Tian, Q., Sun, B.S., Ozguler, A., Morris, S.A., Parametric modeling in food package defect imaging (2000) IEEE Trans. on Ultrasonic, Ferroelectrics and Freq. Contr, 47 (3), pp. 635-643; Wu, H., Sun, D., Zhou, Z., Xiong, S., Model identification of a small-scale air vehicle for loitering control design (2004) Proc. of IEEE Int. Conf. on Robotics and Automation, 4, pp. 4035-4040; Wu, H., Sun, D., Zhou, Z., Model identification of a micro air vehicle in loitering flight based on attitude performance evaluation (2004) IEEE Trans. on Robotics, 20 (4), pp. 702-712; Koivo, A.J., Force-position-velocity control with self-tuning for robotic manipulators (1986) Proc. of IEEE Int. Conf. on Robotics and Automation, 3, pp. 1563-1568; Hori, C., Itakura, K., Nogawa, M., Shirakabe, M., Kubato, I., Tomoike, H., Takatani, S., Estimation of aortic BP waveform from noninvasive radial tomometry; validation of FFT and ARX models (1997) Proc. of 19th IEEE Int. Conf. on EMBS, pp. 1142-1145; Ljung, L., (1987) System identification-Theory for the user, , Prentice Hall, Eaglewood Cliffs, New Jersey; Akaike, H., Information theory as an extension of the Maximum Likelihood principle (1973) 2nd International Symposium on Information Theory, pp. 267-281; He, X., Asada, H., A new method for identifying orders of input-output models for nonlinear dynamic systems (1993) Proc. of the American Control, pp. 2520-2523; Norgaard, M., Neural network based on system identification toolbox, (2000), Technical Report, 00-E-891, Department of Automation, Technical University of DenmarkChungue, E., Boutin, J.P., Roux, J., Antibody capture ELISA for IgM antibody titration in sera for dengue serodiagnosis and survellance (1989) Research in Virology, 140, pp. 229-240; Ibrahim, F., Taib, M.N., Wan Abas, W.A.B., Guan, C.C., Sulaiman, S., A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (2005) Compu. Methods Programs Biomed, 79, pp. 273-281; Herlina, A.R., Fatimah, I., Mohd Nasir, T., A non-invasive system for predicting hemoglobin (Hb) in dengue fever (DF) and dengue hemorrhagic fever (DHF) (2005) Proc. Int. Conf. on Sensor and New Techniques in Pharmaceutical and Biomedical Research (ASIASENSE), , Kuala Lumpur; Abdul Rahim, F.I.H., Taib, M.N., Modeling of hemoglobin in dengue infection application (2006) Journal of Elektrical Engineering (ELEKTRIKA), 8; Abdul Rahim, H., Ibrahim, F., Taib, M.N., Assessment of Autoregressive (AR) models for dengue infection application (2006) Proc. Proc. of the 2nd Int. Colloquium on Signal Processing and its Applications (CSPA 2006), , Cherating, Pahang; Abdul Rahim, H., Ibrahim, F., Taib, M.N., Analysis of linear ARX modeling in the diagnosis of dengue infections (2007) Proc. Proc. of the 1st Int. Conference on Control, Instrumentation and Mechatronics (CIM 07), , Johor Bahru, Johor; Ibrahim, F., Prognosis of dengue fever and dengue haemorrhagic fever using bioelectrical impedance, (2005), Ph.D dissertation, Department of Biomedical Engineering,University of Malaya, JulyN1 - Sponsors: IEEE
Uncontrolled Keywords: Composite structures, Information technology, Appropriate models, ARMAX models, Autoregressive, Autoregressive moving averages, Exogenous inputs, Final prediction errors, Haemoglobin, Lipschitz, Hemoglobin
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 26 Mar 2014 02:24
Last Modified: 01 Nov 2017 04:00

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