Research Article
Effects of Exercise in Diabetic Rats Using Continuous Wavelet Transform
@INPROCEEDINGS{10.1007/978-3-319-04102-5_5, author={Dimitrios Tsalikakis and Ioannis Nakos and Alexandros Tzallas and Evagelos Karvounis and Markos Tsipouras}, title={Effects of Exercise in Diabetic Rats Using Continuous Wavelet Transform}, proceedings={Ambient Media and Systems. Third International ICST Conference, AMBI-SYS 2013, Athens, Greece, March 15, 2013, Revised Selected Papers}, proceedings_a={AMBI-SYS}, year={2014}, month={6}, keywords={HRV Diabetic Exercise Continuous Wavelet Transform Wavelet Entropy}, doi={10.1007/978-3-319-04102-5_5} }- Dimitrios Tsalikakis
Ioannis Nakos
Alexandros Tzallas
Evagelos Karvounis
Markos Tsipouras
Year: 2014
Effects of Exercise in Diabetic Rats Using Continuous Wavelet Transform
AMBI-SYS
Springer
DOI: 10.1007/978-3-319-04102-5_5
Abstract
This paper explores an approach to study entropy differentiations of heart’s activities estimation in Low Frequency (LF) and High Frequency (HF) bands. Dataset composed of 34 ECGs, obtained from healthy and diabetic rats under normal and exercise living conditions. RR intervals extracted efficiently in order to create Heart Rate (HR) time series. Continuous Wavelet Transform (CWT) has been used, as the most appropriate approach, to evaluate the effects of exercise on healthy and diabetic HR variability (HRV). Statistical analysis performed taking into account both wavelet entropy in the low and the high frequency selected bands and the corresponding index LF/HF of the wavelet coefficients. Our results show that wavelet entropy measure based on CWT decomposition can capture significant differences between the specific frequency regions that are intrinsically related to the structure of the RR signal. According to our analysis, diabetic rats living under exercise conditions appear to have a reduced LF/HF entropy ratio compared to healthy population.