Evaluation of ECG Signals for Mental Stress Assessment using Fuzzy Technique
G. Ranganathan1, R. Rangarajan2, V. Bindhu3 

1G. Ranganathan, Associate Professor, Department of ECE, RVS Faculty of Engineering, Coimbatore, India.
2Dr. R. Rangarajan, Dean, Dr. Mahalingam college of Engineering and Technology, Coimbatore, India.
3V. Bindhu, Assistant Professor, Department of ECE, PPG Institute of Technology, Coimbatore, India.
Manuscript received on August 19, 2011. | Revised Manuscript received on August 29, 2011. | Manuscript published on September 05, 2011. | PP: 195-201 | Volume-1 Issue-4, September 2011. | Retrieval Number: D0121081411/2011©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper presents the evaluation of mental stress assessment using heart rate variability. The activity of the autonomic nervous system (ANS) is studied by means of frequency analysis of the Electrocardiogram (ECG) signal. Spectral decomposition of the Heart Rate Variability before smoking and after smoking was obtained. Mental stress is accompanied by dynamic changes in ANS activity. ECG signal analysis is popular for assessing the activities of autonomic nervous system. The approach consists of 1) Recording the ECG signals, 2) Signal processing using wavelets, 3) Fuzzy evaluation techniques to provide robustness in ECG signal analysis, 4) Monitoring the function of ANS under different stress conditions. Our experiment involves 20 physically fit persons under different conditions. Fuzzy technique has been used to model the experimental data.
Keywords: Adaptive Neuro Fuzzy Inference System (ANFIS), Non-linear System, Electrocardiogram (ECG), Autonomic Nervous System(ANS).