Wavelet transform analysis of heart rate variability during myocardial ischaemia

2002 ◽  
Vol 40 (1) ◽  
pp. 72-78 ◽  
Author(s):  
L. G. Gamero ◽  
J. Vila ◽  
F. Palacios
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wavelet Transform ◽  
Myocardial Ischaemia ◽  
Wavelet Transform Analysis

scholarly journals Wavelet transform analysis of heart rate variability during dipyridamole-induced myocardial ischemia: Relation to angiographic severity and echocardiographic dyssynergy

1999 ◽  
Vol 22 (3) ◽  
pp. 201-206 ◽  
Author(s):  
Mario Petretta ◽  
Letizia Spinelli ◽  
Fortunato Marciano ◽  
Maria L. Vicario ◽  
Gianluca Testa ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wavelet Transform ◽  
Myocardial Ischemia ◽  
Wavelet Transform Analysis

Wavelet transform analysis of heart rate variability to assess the autonomic changes associated with spontaneous coronary spasm of variant angina

2003 ◽  
Vol 36 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Bi-Hua Tan ◽  
Hiroki Shimizu ◽  
Kenji Hiromoto ◽  
Yoshio Furukawa ◽  
Mitsumasa Ohyanagi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wavelet Transform ◽  
Coronary Spasm ◽  
Variant Angina ◽  
Autonomic Changes ◽  
Wavelet Transform Analysis

Estimation of Heart Rate Variability Fluctuations by Wavelet Transform

2011 ◽  
Vol 57 (3) ◽  
pp. 395-400 ◽  
Author(s):  
Anton Popov ◽  
Yevgeniy Karplyuk ◽  
Volodymyr Fesechko
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wavelet Transform ◽  
Experimental Results ◽  
Dyadic Wavelet ◽  
Heart Rate Fluctuations ◽  
Slow Heart Rate ◽  
Dyadic Wavelet Transform

Estimation of Heart Rate Variability Fluctuations by Wavelet TransformTechnique for separate estimation of fast and slow fluctuations in the heart rate signal is developed. The orthogonal dyadic wavelet transform is used to separate the slow heart rate changes in approximation part of decomposition and fast changes in detail parts. Experimental results using the recordings from persons practicing Chi meditation demonstrated the applicability of estimation heart rate fluctuations with the proposed approach.

Preoperative heart rate variability fails to predict the occurrence of postoperative myocardial ischaemia and cardiac events

1994 ◽  
Vol 8 (3) ◽  
pp. 140
Author(s):  
S.C.U. Marsch ◽  
B. Naegeli ◽  
K. Skarvan ◽  
H-G. Schaeler ◽  
I. Castelli ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Myocardial Ischaemia ◽  
Cardiac Events

Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method

2015 ◽  
Vol 81 ◽  
pp. 56-64 ◽  
Author(s):  
U. Rajendra Acharya ◽  
K. Sudarshan Vidya ◽  
Dhanjoo N. Ghista ◽  
Wei Jie Eugene Lim ◽  
Filippo Molinari ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Computer Aided Diagnosis ◽  
Discrete Wavelet ◽  
Transform Method ◽  
Computer Aided ◽  
Aided Diagnosis

Wavelet transform to quantify heart rate variability and to assess its instantaneous changes

1999 ◽  
Vol 86 (3) ◽  
pp. 1081-1091 ◽  
Author(s):  
Vincent Pichot ◽  
Jean-Michel Gaspoz ◽  
Serge Molliex ◽  
Anestis Antoniadis ◽  
Thierry Busso ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Fourier Transform ◽  
Wavelet Transform ◽  
Wavelet Transforms ◽  
Autonomous Nervous System ◽  
Dynamic Changes ◽  
Nonstationary Signals ◽  
Higher Doses

Heart rate variability is a recognized parameter for assessing autonomous nervous system activity. Fourier transform, the most commonly used method to analyze variability, does not offer an easy assessment of its dynamics because of limitations inherent in its stationary hypothesis. Conversely, wavelet transform allows analysis of nonstationary signals. We compared the respective yields of Fourier and wavelet transforms in analyzing heart rate variability during dynamic changes in autonomous nervous system balance induced by atropine and propranolol. Fourier and wavelet transforms were applied to sequences of heart rate intervals in six subjects receiving increasing doses of atropine and propranolol. At the lowest doses of atropine administered, heart rate variability increased, followed by a progressive decrease with higher doses. With the first dose of propranolol, there was a significant increase in heart rate variability, which progressively disappeared after the last dose. Wavelet transform gave significantly better quantitative analysis of heart rate variability than did Fourier transform during autonomous nervous system adaptations induced by both agents and provided novel temporally localized information.

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