ECG Signal Processing using Dyadic wavelet for Mental Stress Assessment

摘要：

This paper presents the evaluation of mental stress assessment using heart rate variability. The heart rate signals are processed first using Fourier transform, then it is applied to wavelet transform. The activity of the autonomic nervous system is noninvasively studied by means of autoregressive (AR) frequency analysis of the heart-rate variability (HRV) signal. Spectral decomposition of the Heart Rate Variability during whole night recordings was obtained, in order to assess the characteristic fluctuations in the heart rate. 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 using the Dyadic wavelet.

作者: G.Ranganathan V.Bindhu R.Rangarajan

作者单位: Karpagam College of Engineering, Coimbatore, Tamilnadu Sri Ramakrishna Engineering College, Coimbatore, Tamilnadu

会议类型: 国际会议

会议名称: The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-06-18（万方平台首次上网日期，不代表论文的发表时间）