Title :
ECG Signal Processing Using Dyadic Wavelet for Mental Stress Assessment
Author :
Ranganathan, Gopi ; Bindhu, V. ; Rangarajan, Rajes
Author_Institution :
Karpagam Coll. of Eng., Coimbatore, India
Abstract :
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.
Keywords :
Fourier transforms; autoregressive processes; electrocardiography; fluctuations; fuzzy systems; medical signal processing; wavelet transforms; ECG; Fourier transform; HRV analysis; autonomic nervous system; autoregressive frequency analysis; characteristic fluctuations; dyadic wavelet transform; fuzzy clustering; heart rate variability; mental stress assessment; signal processing; spectral decomposition; Autonomic nervous system; Electrocardiography; Fourier transforms; Frequency; Heart rate; Heart rate variability; Human factors; Signal analysis; Signal processing; Wavelet transforms;
Conference_Titel :
Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4712-1
Electronic_ISBN :
2151-7614
DOI :
10.1109/ICBBE.2010.5516360
