Evolved fuzzy reasoning model for hypoglycaemic detection

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Volumn , Issue , 2010, Pages 4662-4665

  Ling, S H ^a   Nuryani, ^a   Nguyen, H T ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL STUDY; DATA SETS; DEPARTMENT OF HEALTHS; EARLY DETECTION; ELECTROCARDIOGRAM SIGNAL; FUZZY MEMBERSHIP FUNCTION; FUZZY REASONING; HEART RATES; HYBRID PARTICLE SWARM OPTIMIZATION; HYPOGLYCAEMIA; HYPOGLYCAEMIC; INSULIN THERAPY; MUTATION OPERATIONS; PHYSIOLOGICAL PARAMETERS; SENSITIVITY AND SPECIFICITY; SIDE EFFECT; TYPE 1 DIABETES MELLITUS; WESTERN AUSTRALIA;

ALGORITHMS; MEMBERSHIP FUNCTIONS; PARTICLE SWARM OPTIMIZATION (PSO); PHYSIOLOGY;

PHYSIOLOGICAL MODELS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; ELECTROCARDIOGRAPHY; FUZZY LOGIC; HUMAN; HYPOGLYCEMIA; INSULIN DEPENDENT DIABETES MELLITUS; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; DIABETES MELLITUS, TYPE 1; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROCARDIOGRAPHY; FUZZY LOGIC; HUMANS; HYPOGLYCEMIA; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 78650848912     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2010.5626450     Document Type: Conference Paper

References (11)

1. D.G. Altman and J.M. Bland, "Statistics Notes: Diagnostic tests 1: sensitivity and specificity," British Medical Journal, no. 308, pp. 1552-1552, 1994.
2. DCCT Research Group, "Adverse events and their association with treatment regimens in the Diabetes Control and Complications Trial", Diabetes Care, no. 18, pp. 1415-1427, 1995.
3. G. Heger, K. Howrka, H. Thoma, G. Tribl, and J. Zeitlhofer, "Monitoring set-up for selection of parameters for detection of hypoglycaemia in diabetic patients," Med. & Biol. Eng. & Comp., vol. 34, pp. 69-75, 1986.
4. J.S. Jang and C.T. Sun, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall, 1997.
5. S.H. Ling, H.C.C. Iu, K.Y. Chan, H.K. Lam, C.W. Yeung and F.H.F Leung, "Hybrid particle swarm optimization with wavelet mutation and its industrial applications," IEEE Trans. Sys., Man, and Cybernetics, Part B, vol. 38, no.3, pp. 743-763, Jun. 2008.
6. H. Mamdani and S. Assilian, "An experiment in linguistic synthesis with a fuzzy logic controller," International Journal of Man-Machine Studies, vol. 7, no. 1, pp. 1-13, 1975.
7. H.T. Nguyen, "Intelligent technologies for real-time biomedical engineering applications", Int. J. Automation and Control, vol. 2, no. 2, pp. 274-285, 2008.
8. H.T. Nguyen, N. Ghevondian, T. Jones, "Detection of nocturnal hypoglycaemic episodes (natural occurrence) in children with type 1 diabetes using an optimal Bayesian neural network algorithm", in 30th Ann. Int. Conf. of the IEEE Engineering in Medicine and Biology Society, Vancouver, Canada, Aug 2008, pp. 1311-1314.
9. J.C. Pickup, "Sensitivity glucose sensing in diabetes", Lancet, no. 355, pp. 426-427, 2000.
10. G.A.F. Seber, Linear regression analysis. Wiley, 2003.
11. B. Widrow and M.A. Lehr, "30 years of adaptive neural networks: Perceptron, madaline, and backpropagation," Proceedings of the IEEE, vol. 78, no. 9, pp. 1415-1442, Sept. 1990.