DocumentCode :
3587509
Title :
Non-linear feature extraction of 24-hours HRV data based on circadian rhythm
Author :
Tajane, Kapil ; Pitale, Rahul ; Umale, Jayant
fYear :
2014
Firstpage :
1
Lastpage :
5
Abstract :
From few decades ECG signal is used as a baseline to determine the hearts condition. It is very much essential to detect and process ECG signal accurately. Heart Rate Variability (HRV) is an effective mechanism to analyze the cardiac health of a patient. In this paper we proposed new technique to detect linear as well as non-linear characteristics of 24 hour HRV data based on circadian rhythm. A circadian rhythm is nothing but a approximately 24 hour clock present in living beings within the physiological process, which affects the HRV. The motivation of this paper is to define the set of rules for 24 hour HRV data, so that it will be easily applicable. As HRV is self similar, so we have to find the self similarity of 24 hour HRV data into 5-10 min of HRV data.
Keywords :
electrocardiography; feature extraction; medical signal detection; ECG signal detection; ECG signal processing; HRV data; cardiac health analysis; circadian rhythm; heart rate variability; linear characteristics; nonlinear characteristics; nonlinear feature extraction; physiological process; time 24 hour; time 5 min to 10 min; Electrocardiography; Feature extraction; Heart rate variability; Multiresolution analysis; Support vector machines; Wavelet transforms; Chaos; Circadian rhythm; ECG; Fractal; HRV; KDD; Lyapunov Exponent; Phase Space; Wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Convergence of Technology (I2CT), 2014 International Conference for
Print_ISBN :
978-1-4799-3758-5
Type :
conf
DOI :
10.1109/I2CT.2014.7092205
Filename :
7092205
Link To Document :
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