Connectionist Expert System to Diagnose Neck and Arm Pain

  • S. Thamarai Selvi Manonmaniam Sundaranar University, Tirunelveli.
Keywords: Neurophysiology, Physiology, Medical sciences

Abstract

A connectionist expert system (CES) called BIONET aimed at assisting physicians in the diagnosis of diseases, such as neck and arm pain has been proposed. BIONET is an artificial network or connectionist network model capable of classifying diseases. Need for the development of CES for defence personnel has been discussed: BIONET is a feedforward three layer neural network with one hidden layer. The input, layer has been designated as stimulus layer, the hidden layer as receptor layer and output layer ag cortical layer. The sequential connections with spatial orientation have been maintained between stimulus layer and receptor layer for each specific factor. Parallel connections are established only at the cortical layer. Direct firing and facilitatory and inhibitory mechanisms are adhered to the neurophysiology of human nervous system. An algorithm for training on BIONET is also given. BIONET is simulated on a digital computer with training samples of patients collected from various hospitals in Tamil Nadu to diagnose neck and arm pain,diseases for testing purpose.

Author Biography

S. Thamarai Selvi, Manonmaniam Sundaranar University, Tirunelveli.
Mrs S Thamarai Selvi obtained her BE (Mechanical Engineering) form Alagappa Chettiar College of Engineering and Technology, Kara~kudi and ME (Computer Science & Engg) from Government College of Technology, Coimbatore with first rank. She is a member of the Boards of Studies (PG & UG) of M.S.University, Tirunelveli, and Sri. Parasakthi College (Autonomous), Courtalam. She has completed a UGC project titled 'Study of signs and symptoms for neck and arm pain and input design for neural network'.Since 1994, she has been working as a Reader in the Department of Computer Science, Manonmaniam Sundaranar University, Tirunelveli. Her area of research include artificial neural network. She has presentedmore than 10 papers in national/international conferences. She is a life member of the Computer Society of India (CSI), Indian Society for Technical Education (ISTE) and Institution of Engineers (IE).She is co-author of the book titled Engineering Drawing in First Angle Projection.

References

Wasserrnan, Philip D. Neural computing: Theory and practice. Van Nostrand Reinhold, New York. 1989. p. 47.

Bronzino, Joseph D. The biomedical engineering handbook. CRC Press Inc, USA, 1995. p. 1.

Kandasamy, A. & Sukesh Kumar, A. Role of medical expert systems in health care in the Indian context. DeJ: Sci. J., 1997, 47(4), 499- 503.

Ingalhalikar, V.T. Neck pain and related problems. Merck E. Ltd. India. 1994, pp. 1 1-14.

Nakano, Kenneth K. Neck pain. In Text book of rheumatology, Ed. 2. Saunders Publications, 1985. pp. 416-35.

Ramamurthy, Somayaji. Cervical pain. In Practical management of pain year book, edited by Prithivi Raj P. Medical Publishers Inc., 1986. pp. 418-42.

Rogers, W. et al. Computer-aided medical diagnosis: Literature review. Int. J. Biomedi. Comput., 1979, 10, 267-89.

Thamarai Selvi, S. & Ramar, S. Study of signs and symptoms for neck and arm pain and input design for neural network. UGC Minor Research Project, New Delhi, September 1997. 56 p. Report No. UGC-4 AG-96-15.

Kennedy, R.L.; Harrison, R.F. & Burton A.M. An artificial neural network system for diagnosis of acute myocardial infarction in the accident and emergency departments: Evaluation and comparison with serum myoglobin measurements. Comput. Methods Prog. Biomed., 1997, 52(2), 93-103.

Rudzki, K.; Hartleb, M.; Sadowski, T. & Rudzka, J. Focal liver disease: Neural network-aided diagnosis based on clinical and laboratory data.Gastroenterolclinical Biology, 1997, 21(2), 98-102.

Zou, Y.; Shen, Y.; Shu, L. & Wang, Y. Artificial neural network to assist psychiatric diagnosis. Psychiatry, 1996, 169(1), 64-67.

Richard, Lippmann P. An introduction to computing with neural nets. IEEE ASSP Mag., 1987, 3(4), 4-22.

Thamarai Selvi, S.; Ramar, S. & Arumugam, S. Diagnosis of cervical spondylosis using neural networks. In Proceedings of the National Conference on Microcomputer Systems, 18-19 February 1995, Trivandrum Chapter of Computer Society of India, Trivandrum, 1995. pp.1-4.

Dalal, P.M. Decade of brain: 2000 AD. In Medicine update gold apicon-95, Vol. V, edited by P.S. Shankar. The Association of Physicians of India, 1995. pp. 347-52.

Arthur, Guyton C. Text book of medical physiology, Ed, 8. Prism Books (Pvt.) Ltd., Bangalore, 1991. p. 495.

Simon, Haykin. Neural networks: A comprehensive foundation. IEEE Press, 1992. p. 22.

Robert, Hecht-Nielsen. Neurocomputing. Addison-Wesley Publishing Comp., NewYork, 1991. p. 122.

Bernard, Widrow & Michael, A. Lehr. 30 Years of adaptive neural networks: Perceptron, madaline and back propagation. Proceedings IEEE, September 1990, 78(9), 1415-42.

Funahashi, K. On the approximate realisation of continuous mappings by neural networks. Neural

Networks, 1989, 2(3), 183-92.

Cybenko, G. Approximation by superpositions of a sigmoidal function. Math. Control Signals Syst.,1989, 2,303-14.

Hornik, K.; Stinchcombe, M. & White, H. Multilayer feedforward networks are universal approximators. Neural Networks, 1989, 2, 359- 66.

Neil, E. Cotter. The Stone-Weierstrass theorem and its application to neural networks. ZEEE Trans. Neural Netw., 1990, 1, 290-95.

Charles, F. Stevens. The neuron. In Neuro control systems theory and applications, edited by M.M. Gupta, and D.H. Rao. 1995, pp. 101-11.

Mountcastle, Vernon, B. (Ed). Sensory receptors and neural encoding: Introduction to sensory process. In Medical physiology, Vol. 1. 1980. pp. 327-47.

Rumelheart, D.E.; Hinton, G.E. & Williams, R.J. Learning internal representations by error propagation. In Parallel distributed processing: Explorations in the microstructure of cognition, Vol.1, edited by D.E. Rumelhart and J.L. McClelland. MIT Press, Cambridge, 1986. pp. 318-62.

Thamarai Selvi, S.; Ramar, S. & Arumugam, S. BIONET. In Robotics, vision and parallel processing for industrial automation, edited by P.A. Venkatachalam. Proceedings of the International Conference, 28-30 November 1996, Universiti Sains Malaysia, Perak, Malaysia, 1996. ' pp. 394-99.

Thamarai Selvi, S.; Ramar, S. & Arumugam, S. Connectionist expert system for neck and arm pain diagnosis. In Automation, edited by Pradeep K. Chande, A.K. Ramani.; Shubhalaxmi Kher and Nirmal Dagdee. Proceedings of the International Conference, 12- 14 December 1995, Shri G. S. Institute of Technology and Science, Indore. Allied Publishers, 1995. pp. 5-7.

Thamarai Selvi, S.; Ramar, S. & Arumugam, S. Neck and arm pain evaluation using neural network. In Recent trends in applied systems reaserch, edited by P. Radhakrishnan, G. ' Gurusamy, Proceedings of the Nineteenth National Systems Conference, 14-16 December 1995, PSG College of Technology, Coimbatore, Allied Publishers, 1995. pp. 532-36.

Published
2013-01-01
How to Cite
SelviS. (2013). Connectionist Expert System to Diagnose Neck and Arm Pain. Defence Science Journal, 49(3), 197-210. https://doi.org/10.14429/dsj.49.3829
Section
Biomedical Sciences