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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 52-585
Full Name: Santhi Chelladurai
Position: Associate Professor
Age: ON
Sex: Female
Address: Govt. College of Technology, Coimbatore
Country: INDIA
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E-mail address: cs2002cbe@yahoo.co.in
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Title of the Paper: Intrinsic time scale analysis of Heart rate variability
Authors as they appear in the Paper: C.Santhi, N.kumaravel
Email addresses of all the authors: cs2002cbe@yahoo.co.in,kumaravel_n@annauniv.edu
Number of paper pages: 10
Abstract: The analysis of heart rate variability (HRV) demands specific capabilities which are not provided either by parametric or nonparametric conventional spectral estimation methods. The principle objective of this paper is to identify the intrinsic time scales that change with age and pathological conditions. The key part of the method is the Empirical mode decomposition, in which the complicated HRV data can be adaptively decomposed into a finite and often small number of intrinsic time scales. EMD decomposes half an hour HRV signal into nine intrinsic time scales. The average period and energy density function of intrinsic time scales are computed as time domain measures. As a specific application the method is applied to HRV of 20 healthy young control subjects, 20 healthy old control subjects, 20 congestive heart failure patients and 33 long term ST patients. The main advantage of this method is, it does not make any prior assumption about the HRV signal being anal!
yzed and no artificial information is introduced into the filtering method. The healthy young control subject's absolute and normalized energy scaling pattern provide a reference for detecting changes or differences in the scaling pattern of healthy old and patients groups. The results show that the average period and energy density of the lowest intrinsic time scale decreases with pathological conditions and aging. The average period of the lowest intrinsic time scale discriminates healthy control group and patients group with a sensitivity of 100% and specificity of 85%. The observed high sensitivity of the method makes it a promising approach to be used as a screening test in clinical practice for specific risk-groups.
Keywords: Average period, Autonomous nervous system, Empirical Mode Decomposition, Energy density function, Heart Rate Variability, Intrinsic time scales, RR intervals, Scaling pattern
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How Did you learn about congress: Biomedical signal processing
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