Logo PTI
Polish Information Processing Society
Logo RICE

Annals of Computer Science and Information Systems, Volume 10

Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering

Design of Diagnosis and Monitoring System of Heart Related Diseases using Fuzzy Inference System

, ,

DOI: http://dx.doi.org/10.15439/2017R22

Citation: Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering, Vijender Kumar Solanki, Vijay Bhasker Semwal, Rubén González Crespo, Vishwanath Bijalwan (eds). ACSIS, Vol. 10, pages 321–327 ()

Full text

Abstract. Human desire increases day-by-day in different aspects. It requires the technology to be compatible accordingly. Fast and user friendly access are major challenges for different applications. One of the applications is hospital management for patient care, diagnosis and treatment. Modern health care provide different type of provision for people using electronic media. Recently research explores the cardiac diagnosis and care using modern equipment and facilities. In this paper an approach has been considered to diagnose heart diseases in an intelligent manner. The model is designed using fuzzy logic in which the rule based principle is applied to satisfy the objective. Keeping view on multi agent system the model is developed. The diagnosis of the patient is performed using Fuzzy Inference System (FIS). Once the pathological test results are obtained these will help to form the rules of the model and it works for the diagnosis in convenient way. Further the result of detection is communicated through internet or SMS for monitoring and post care purpose. The simulated result shows its performance that can be helpful to the physicians as well as the patients from distant places.

References

  1. H. D Lee, A. Rabbi, J. Choi, and R. F. Rezai, “Development of a Mobile Phone Based e-Health Monitoring Application,” International Journal of Advanced Computer Science and Applications, vol. 3, no. 3, pp. 38-43,2012.
  2. J. C. Su, “Mobile multi-agent based, distributed information platform (MADIP) for wide-area e-health monitoring”, Computers in Industry, vol. 59, pp: 55–68, 2008.
  3. N. Benhajji, D.Roy, and D. Anciaux, “Patient-centered multi agent system for health care”,IFAC-Papers On Line, vol. 48, no. 3, pp: 710–714, 2015.
  4. G. B. Silverman, N. Hanrahan, G. Bharathy, K. Gordon K, and D. Johnson, “A systems approach to healthcare: Agent-based modeling,community mental health, and population well-being”, Artificial Intelligence in Medicine,vol. 63, pp. 61–71, 2015.
  5. H. O. Al-Sakran, “Framework architecture for improving healthcare information systems using agent technology”, International Journal of Managing Information Technology,vol.7, no.1, pp. 17-31,February2015
  6. K. AlSharqi, A. Abdelbari,,A. Abou-Elnour, and M. Tarique M, “Zigbee based wearable remote healthcare monitoring system for elderly patients” International Journal of Wireless & Mobile Networks (IJWMN), 2014; June, Vol. 6, No. 3, pp-53-67.
  7. M. N. Mohanty, “An Efficient Design for Low Cost Cardio-Monitoring System”, Adv. Science Letters, vol.22, Iss. 2, pp. 349-353,2016
  8. S. S. Biswal, M. N. Mohanty, B. Sahu, and S. Das, “Unconscious State Analysis Using Intelligent Signal Processing Techniques”, Adv. Science Letters, vol.22, Iss. 2, pp. 314-318,2016
  9. A. Das, S. S. Biswal,S. Shalinee, and M. N. Mohanty, “Design of Telemedicine System for Brain Signal Analysis”, IJTMCP, Inder Sc. Pub., vol.1, no. 3,2016
  10. M. Singh, M. N. Mohanty, and R. N. D. Choudhury, “An Embedded Design for Patient Monitoring and Telemedicine”,Int.Journal of Electrical, Electronics & Computer Engineering”, vol. 2, no. 2, pp. 66-71, 2013.
  11. C. S. Devi, G. G. Ramani,and J. A. Pandian, “Intelligent E-Healthcare Management System in Medicinal Science”, International Journal of PharmTech Research, vol. 6, no.6, pp. 1838-1845,Oct-Nov. 2014.
  12. E. E. Elavathingal, and T.K Sethuramalingam, “A Survey of E-Healthcare Systems Using Wearable Devices and Medical Sensor Networks”, Karpagam journal of engineering research (KJER),vol1,no.1Iss. 1,2014.
  13. S. Tupe, and N. P. Kulkarni, “ECA: Evolutionary Computing Algorithm for E-Healthcare Information System”, SPPU, Pune iPGCON-2015.
  14. S. A. Hannan, A. V. Mane, R. R. Manza, and R. J. Ramteke, “Prediction of heart disease medical prescription using radial basis function”,978-1-4244-5967-4/10/$26.00 © IEEE, 2010.
  15. M. Shouman, T. Turner, and R. Stocker, “Using Decision Tree for Diagnosing Heart Disease Patients”,Conferences in Research and Practice in Information Technology (CRPIT),vol. 121, pp. 23-29,2011.
  16. M. Shouman, T. Turner, and R. Stocker, “Applying k-Nearest Neighbour in Diagnosing Heart Disease Patients”,International Journal of Information and Education Technology,vol. 2, no. 3, pp. 220-223,June 2012.
  17. D. Mandal, I. M. Chattopadhyay, and S. Mishra, “A Low Cost Non-invasive Digital Signal Processor Based (TMS320C6713) Heart Diagnosis System”, 1st Int’l Conf. on Recent Advances in Information Technology, RAIT-2012.
  18. B. Venkatalakshmi, and M.V. Shivsankar, “Heart Disease Diagnosis Using Predictive Data mining”International Journal of Innovative Research in Science, Engineering and Technology,vol. 3, Special Iss. 3, pp. 1873-1877,March2014.
  19. Z. F. Fitrilina, and H. I. K. Kamil, “Prototype Early Warning System for Heart Disease Detection UsingAndroid Application”, 978-1-4244-7929-0/14/$26.00 ©2014, IEEE, pp. 3468-3471, 2014.
  20. Q. A. Rahman, L. G. Tereshchenko, M. Kongkatong, T. M. Abraham, M. R. Abraham, and H. Shatkay, “Utilizing ECG-Based Heartbeat Classification for Hypertrophic Cardiomyopathy Identification”, IEEE transactions on nanobioscience, vol. 14, no. 5, pp. 505-512, July 2015.
  21. A. Forkan, I. Khalil, T. Z. Zahir, “Context-aware Cardiac Monitoring for Early Detection of Heart Diseases”, Computing in Cardiology; vol. 40, pp.277-280, 2013.
  22. L. Sarangi, M. N. Mohanty and S. Patnaik “Design of MLP Based Model for Analysis of Patient Suffering from Influenza” Proceedia Computer Science, Elsevier, 92, 2016; pp-396-403.
  23. L. Sarangi, M. N. Mohanty and S. Patnaik “An Intelligent Decision Support System for Cardiac Disease Detection” International Journal of Control Theory and Applications, 8(5), 2015; pp. 2137-2143.
  24. L. Sarangi, M. N. Mohanty and S. Patnaik “Critical Heart Condition Analysis through Diagnostic Agent of e-Healthcare System using Spectral Domain Transfom” Indian Journal of Science & Technology, Vol 9(38) 2016; pp. 1-6
  25. Semwal, Vijay Bhaskar, Pavan Chakraborty, and Gora Chand Nandi. "Less computationally intensive fuzzy logic (type-1)-based controller for humanoid push recovery." Robotics and Autonomous Systems 63 (2015): 122-135.
  26. Kumari, Pinki, and Abhishek Vaish. "Information-theoretic measures on intrinsic mode function for the individual identification using EEG sensors." IEEE Sensors Journal 15.9 (2015): 4950-4960.
  27. Kumari, Pinki, and Abhishek Vaish. "Feature-level fusion of mental task’s brain signal for an efficient identification system." Neural Computing and Applications 27.3 (2016): 659-669.