Friday 26th of April 2024
 

Performance Evaluation of Generalized Feedforward Neural Network Based ECG Arrhythmia Classifier


Shivajirao M. Jadhav, Sanjay L. Nalbalwar and Ashok A. Ghatol

Evaluation is the key to making real progress in machine learning. In this paper we have evaluated performance of our proposed a classifier for cardiac arrhythmia disease classification from standard 12 lead ECG recordings data, using a Generalized Feedforward Neural Network (GFNN) model. The proposed classifier is trained using static backpropagation algorithm to classify arrhythmia cases into normal and abnormal classes. In this study, we are mainly interested in producing high confident arrhythmia classification results to be applicable in diagnostic decision support systems. In arrhythmia analysis, it is unavoidable that some attribute values of a person would be missing. Therefore we have replaced these missing attributes by closest column value of the concern class. Networks models are trained and tested for UCI ECG arrhythmia data set. This data set is a good environment to test classifiers as it is incomplete and ambiguous bio-signal data collected from total 452 patient cases. The classification performance is evaluated using six measures; sensitivity, specificity, classification accuracy, mean squared error (MSE), receiver operating characteristics (ROC) and area under curve (AUC). The experimental results presented in this paper show that up to 82.35% testing classification accuracy can be obtained.

Keywords: Accuracy, ECG arrhythmia, generalized feedforward neural network model, machine learning, momentum learning rule, sensitivity, specificity.

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ABOUT THE AUTHORS

Shivajirao M. Jadhav
Shivajirao M. Jadhav has received B.E. (Computer Science & Engineering) in 1993 from SGGS College of Engineering and Technology, Nanded India and M.E. (Computer Engineering) in 2003 from VJTI, Mumbai India. He is presently working as Assistant Professor of Information Technology Department at Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, Maharashtra, India. He is doing his Ph.D. study in Computer Engineering Department in the same University through UGC’s Faculty Improvement Program (FIP). His area of interest includes signal data analysis using machine learning and soft computing techniques, real time distributed databases.

Sanjay L. Nalbalwar
Dr. Sanjay L. Nalbalwar has received B.E. (Computer Science & Engineering) in 1990 and M.E. (Electronics) in 1995 from SGGS College of Engineering and Technology, Nanded India. He has completed Ph.D. from IIT Delhi in 2008. He has around 20 years of teaching experience and is working as an Assistant Professor of Electronics & Telecommunication Engineering Department at Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, Maharashtra (India). His area of interest includes Multirate signal processing and Wavelet, stochastic process modeling.

Ashok A. Ghatol
Dr. Ashok A. Ghatol Done his B.E. (Electrical) from Nagpur University, M.Tech. (Electrical), Ph.D Electrical from IIT, Bombay. An academician par excellence, an excellent research guide, philosopher, winner of best Teacher Award, an avid traveler, Shri Ghatol has been actively involved over the last 33 years in the field of Technical Education as an Academician, Researcher, Teacher, Planner and Administrator. His illustrious career spans multiple leadership roles including former Vice-Chancellor of Dr. Babasaheb Ambedkar Technological University, Lonere-Raigad. He has served as a Principal, COEP from 2001-2005 and as a Principal at Government College of Engineering, Amravati from 1994-2001. He has lectured extensively in various National and International Conferences and has earned unique honors and distinctions. He has also received a Quality Environment Award in the year 2002. He has to his credit 15 PhD Students, 3 books and till today a number of research scholars are working under him for their PhD. Degree. His research work has been published in various international and national journals, as well as in various conferences reports. Taking into consideration his active involvement in technical education, AICTE also entrusted a responsibility on him, to Act as the Chairman of Western Regional Council He was Vice-Chairman of ISRE for advising and assisting the council on issues and strategies on quality and quantity in the field of technical education. He was adjusted as an Eminent Executive Member of Indian Society of Technical Education, New Delhi.


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