Development of an FPGA based Smart Embedded System for Rural Telediagnostic Applications

Abstract

The convergence of artificial intelligence based data processing techniques with information and communication technologies has enabled the development of a smart diagnostic system that can be used to provide health care support in remote rural areas. The paper focuses on the development of a smart diagnostic system that can predict the physiological state of a patient given the past physiological data. The smart system has been implemented on an Altera Cyclone EP1K6Q240C8 FPGA chip. Since patients' data randomly vary, therefore no crisp opinion can be made about the physiological state of a patient knowing only the present data. The system employs a smart agent whose role is to monitor and diagnose on a regular time basis and assist the health care professionals in the process of therapeutic decisions. The paper provides an introduction to the notion of smart agent based telemedicine. An extended example on the problem of monitoring renal patients using Body Mass Index (BMI), blood glucose, urea, creatinine, systolic and diastolic blood pressure has been presented in this paper. The system has been tested with height, weight, blood glucose, urea, creatinine, systolic and diastolic blood pressure data of patients where all data other than height have been taken at 10 days interval. Applying the methodology, the chance of attainment of critical renal condition of a patient before the patient actually reaches a critical state has been predicted with confidence.

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S Roy Chowdhury

Shubhajit Roy Chowdhury was born on August 27, 1981 in India. He received his BE degree in Information Technology from Vidyasagar University in 2004 and ME degree in Software Engineering from the Department of Information Technology, Jadavpur University in 2006. He is presently a research scholar at the IC Design and Fabrication Centre, Department of Electronics and Telecommunication Engineering, Jadavpur University. His current research interests include development of FPGA based smart embedded systems for medical diagnosis and ASIC design of intelligent signal processing circuits.