A low-cost Diagnostic Support System for remote cardiac healthcare

Revolution in the field of mobile technology has a great impact in rural areas. Unfortunately, such revolution has been overused for communication and entertainment. Specific research efforts towards the amalgamation of mobile technology may result in lucid, affordable, reliable and accurate diagnostic means in the field of healthcare. This paper presents an optimized approach for the development of a low-cost and yet reliable Diagnostic Support System (DSS) for cardiac arrhythmia using an Android based tablet phone. Pre-processed ECG data undergoes the process of feature extraction, based on Polar Teager Energy (PTE) algorithm. Three types of cardiac states viz. `Normal Sinus Rhythm (NSR)', `Atrial Arrhythmia (AAR)' and `Ventricular Arrhythmia (VAR)' have been classified using Artificial Neural Network (ANN). The algorithm has been evaluated using standard ECG database records from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH). A three lead cardio-care system has been developed to measure and transmit the real subject data to the tablet phone for the diagnosis. The results confirmed that the proposed system has excellent performance with 96% overall diagnostic accuracy in spite of constraints on the system due to its low cost.