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

fYear

2010

fDate

18-20 June 2010

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on

Conference_Location

Chengdu

ISSN

2151-7614

Print_ISBN

978-1-4244-4712-1

Electronic_ISBN

2151-7614

Type

conf

DOI

10.1109/ICBBE.2010.5516360

Filename

5516360