Evolving a Bayesian classifier for ECG-based age classification in medical applications
Applied Soft Computing
Review article: Human scalp EEG processing: Various soft computing approaches
Applied Soft Computing
Estimation of fractal signals from noisy measurements usingwavelets
IEEE Transactions on Signal Processing
Dynamic fuzzy neural networks-a novel approach to functionapproximation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive noise cancellation using enhanced dynamic fuzzy neural networks
IEEE Transactions on Fuzzy Systems
A robust design criterion for interpretable fuzzy models with uncertain data
IEEE Transactions on Fuzzy Systems
Fuzzy Evaluation of Heart Rate Signals for Mental Stress Assessment
IEEE Transactions on Fuzzy Systems
On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm
IEEE Transactions on Neural Networks
Enhanced combination modeling method for combustion efficiency in coal-fired boilers
Applied Soft Computing
A hybrid expert system approach for telemonitoring of vocal fold pathology
Applied Soft Computing
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This paper presents the evaluation of mental stress assesment using heart-rate variability (HRV). The activity of the autonomic nervous system (ANS) is studied by means of time-frequency analysis (TFA) of the heart-rate variability 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. HRV analysis is a popular tool for assessing the activities of autonomic nervous system. The approach consists of (1) monitoring of heart rate signals, (2) signal processing using wavelet transform (WT) (different wavelets), (3) neuro fuzzy evaluation techniques to provide robustness in HRV analysis, (4) monitoring the function of ANS under different stress conditions. Our experiment involves 20 physically fit persons under different times (before smoking and after smoking). Nero fuzzy technique have been used to model the experimental data.