A computational insight into cardiac beat-to-beat intervals variability: from normal to pathological
DOI:
https://doi.org/10.24193/subbbiol.2018.2.14Keywords:
computerized instrumentation, electrocardiography, fast Fourier transforms, MATLAB, nonlinear dynamical system.Abstract
Over the past 100 years, electrocardiography (ECG) has provided essential information for diagnosing patients with cardiovascular diseases. Despites the large clinical usefulness of classic paper printed 12-lead ECG, along with the accelerated development of computerized data acquisition, beat-to-beat methods of ECG analysis were developed, providing new information in the field of heart rate variability (HRV). The objectives of the study were to establish HRV parameters behavior in healthy subjects and in diabetes mellitus patients, as well as to evaluate HRV during acute cigarette smoking. The results concluded that HRV parameters describe statistically significant lower values in diabetic patients compared to healthy subjects, signifying a decreased response of the heart conduction system to autonomic stimuli. Concerning smoking, the study concluded that during smoking and ten minutes after, HRV parameters presented lower values than before smoking, as revealed by visual (2D and 3D) and analytical HRV methods. Our study is one of the few in literature that focuses on the acute effects of cigarette smoking, rather than the well-known long term effects of this wide-spread habit.
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