Linear Prediction System in Measuring Glucose Level in Blood
Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.
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 T. Denisova, L. Malinova, Glucose, in: Handb. Opt. Sens. Glucose Biol. Fluids Tissues, Taylor & Francis, 2008: pp. 1–40. doi: 10.1201/9781584889755.ch1.
 E. M. A. A. Trabelsi, M. Boukadoum, C. Fayomi, Blood glucose sensor implant using NIR spectroscopy: Preliminary design study, in: Microelectron. (ICM), 2010 Int. Conf. On, Cairo, 2010: pp. 176–179.
 C. I. Examinations, Facts and figures about diabetes, (2016) 2016. http://www.cie.org.uk/images/268776-facts-and-figures-about-cambridge-international-examinations.pdf (accessed January 01, 2014).
 C. F. So, K. S. Choi, J. W. Y. Chung, T. K. S. Wong, An extension to the discriminant analysis of near-infrared spectra, Med. Eng. Phys. 35 (2013) 172–177. doi: 10.1016/j.medengphy.2012.04.012.
 L. Ben Mohammadi, T. Klotzbuecher, S. Sigloch, K. Welzel, M. Göddel, T.R. Pieber, et al., In vivo evaluation of a chip based near infrared sensor for continuous glucose monitoring., Biosens. Bioelectron. 53 (2014) 99–104. doi: 10.1016/j.bios.2013.09.043.
 S. Sivanandam, M. Anburajan, B. Venkatraman, M. Menaka, D. Sharath, Estimation of blood glucose by non-invasive infrared thermography for diagnosis of type 2 diabetes: An alternative for blood sample extraction, Mol. Cell. Endocrinol. 367 (2013) 57–63. doi: 10.1016/j.mce.2012.12.017.
 C. Review, S. Communication, G. Principles, World Medical Association Declaration of Helsinki. Ethical principles for medical research involving human subjects., Nurs. Ethics. 9 (2002) 105–109.
 A. Caduff, M. Mueller, A. Megej, F. Dewarrat, R.E. Suri, J. Klisic, et al., Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation, Biosens. Bioelectron. 26 (2011) 3794–3800. doi: 10.1016/j.bios.2011.02.034.
 A. Caduff, M.S. Talary, M. Mueller, F. Dewarrat, J. Klisic, M. Donath, et al., Non-invasive glucose monitoring in patients with Type 1 diabetes: A Multisensor system combining sensors for dielectric and optical characterisation of skin, Biosens. Bioelectron. 24 (2009) 2778–2784. doi: 10.1016/j.bios.2009.02.001.
 E. Monte-Moreno, Non-invasive estimate of blood glucose and blood pressure from a photoplethysmograph by means of machine learning techniques, Artif. Intell. Med. 53 (2011) 127–138. doi: 10.1016/j.artmed.2011.05.001.
 M. Aloraefy, J. T. Pfefer, C. J. Ramella-Roman, E.K. Sapsford, In Vitro Evaluation of Fluorescence Glucose Biosensor Response, Sensors. 14 (2014). doi:10.3390/s140712127.
 W. L. Clarke, D. Cox, L. a Gonder-Frederick, W. Carter, S.L. Pohl, Evaluating clnical accuracy of systems for self-monitoring of blood glucose, Diabetes Care. 10 (1987) 622–628.
 W.L. Clarke, D. Cox, L. a Gonder-Frederick, W. Carter, S.L. Pohl, Evaluating clnical accuracy of systems for self-monitoring of blood glucose, Diabetes Care. 10 (1987) 622–628.