Novel methods of faster cardiovascular diagnosis in wireless telecardiology
IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
On the estimation of parameters of Takagi-Sugeno fuzzy filte
IEEE Transactions on Fuzzy Systems
Adaptive fuzzy filtering in a deterministic setting
IEEE Transactions on Fuzzy Systems
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
HSI'09 Proceedings of the 2nd conference on Human System Interactions
Telemedical data acquisition system for use in preventive medicine
HSI'09 Proceedings of the 2nd conference on Human System Interactions
Variational bayes for a mixed stochastic/deterministic fuzzy filter
IEEE Transactions on Fuzzy Systems
A mixture of fuzzy filters applied to the analysis of heartbeat intervals
Fuzzy Optimization and Decision Making
Journal of Network and Computer Applications
Estimation of heart rate signals for mental stress assessment using neuro fuzzy technique
Applied Soft Computing
Cardioids-based faster authentication and diagnosis of remote cardiovascular patients
Security and Communication Networks
Computer Methods and Programs in Biomedicine
Subject-dependent biosignal features for increased accuracy in psychological stress detection
International Journal of Human-Computer Studies
Modeling stress recognition in typical virtual environments
Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare
Applied Soft Computing
Modeling observer stress for typical real environments
Expert Systems with Applications: An International Journal
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Mental stress is accompanied by dynamic changes in autonomic nervous system (ANS) activity. Heart rate variability (HRV) analysis is a popular tool for assessing the activities of autonomic nervous system. This paper presents a novel method of HRV analysis for mental stress assessment using fuzzy clustering and robust identification techniques. The approach consists of 1) online monitoring of heart rate signals, 2) signal processing (e.g., using the continuous wavelet transform to extract the local features of HRV in time-frequency domain), 3) exploiting fuzzy clustering and fuzzy identification techniques to render robustness in HRV analysis against uncertainties due to individual variations, and 4) monitoring the functioning of autonomic nervous system under different stress conditions. Our experiments involved 38 physically fit subjects (26 male, 12 female, aged 18-29 years) in air traffic control task simulations. The subjective rating scores of mental workload were assessed using NASA task load index. Fuzzy clustering methods have been used to model the experimental data. Further, a robust fuzzy identification technique has been used to handle the uncertainties due to individual variations for the assessment of mental stress. [ All rights reserved Elsevier].