Estimation of heart rate signals for mental stress assessment using neuro fuzzy technique

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• 作者：G. Ranganathan^a ;   ; [Author Vitae] ; R. Rangarajan^b ; ^{profrr@gmail.com}  ; [Author Vitae] ; V. Bindhu^c ; ^{ranga02002@yahoo.co.in}  ; [Author Vitae]
• 关键词：Adaptive neuro fuzzy inference system (ANFIS) ; Non-linear system ; Heart-rate variability (HRV) ; Electrocardiogram (ECG) ; Autonomic nervous system (ANS)
• 刊名：Applied Soft Computing Journal
• 出版年：2012
• 期刊代码：9_15684946
• 类别：cp
• 出版时间：August, 2012
• 卷：12
• 期：8
• 页码：1978-1984
• 文件大小：901 K

摘要

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.