56 Copyright © 2017, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 3 DOI: 10.4018/978-1-5225-0660-7.ch003 ABSTRACT The current study deals with the investigation of the efect of long-term endurance training on the autonomic nervous system of healthy adults. ECG was recorded for 5 min under resting condition in a sitting position using an ECG acquisition device for 25 swimmers and 25 age-matched sedentary controls. Heart Rate Variability (HRV) parameters of the volunteers were used for statistical analysis and classifcation using binary classifcation trees and artifcial neural networks. The LF/HF ratio for swimmers and sedentary controls was found to be 0.89 ± 0.32 and 0.94 ± 0.46, respectively. This may be attributed to the vagal dominance due to endurance training in the swimmers. Statistical ECG signal processing and db06 wavelet based processing were performed to understand the efect of swimming on the cardiac health. The signal classifcation results indicated that both the HRV and the processed ECG signal features may be used for the classifcation of the swimmers and the sedentary controls using CART, Boosted tree, Random Forest and neural network algorithms. Non-Linear Analysis of Heart Rate Variability and ECG Signal Features of Swimmers from NIT-Rourkela: A Case Study Anupama Ray Indian Institute of Technology Delhi, India Suraj Kumar Nayak National Institute of Technology Rourkela, India Biswajeet Champaty National Institute of Technology Rourkela, India D. N. Tibarewala Jadavpur University, India Kunal Pal National Institute of Technology Rourkela, India