• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.346-355
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• 2017

Atrial fibrillation (AF) and Congestive heart failure (CHF) are increasingly widespread, costly, deadly diseases and are associated with significant morbidity and mortality. In this study, we analyzed three statistical methods for automatic detection of AF and CHF based on the randomness, variability and complexity of the heart beat interval, which is RRI time series. Specifically, we used short RRI time series with 16 beats and employed the normalized root mean square of successive RR differences (RMSSD), the sample entropy and the Shannon entropy. The detection performance was analyzed using four large well documented databases, namely the MIT-BIH Atrial fibrillation (n=23), the MIT-BIH Normal Sinus Rhythm (n=18), the BIDMC Congestive Heart Failure (n=13) and the Congestive Heart Failure RRI databases (n=25). Using thresholds by Receiver Operating Characteristic (ROC) curves, we found that the normalized RMSSD provided the highest accuracy. The overall sensitivity, specificity and accuracy for AF and CHF were 0.8649, 0.9331 and 0.9104, respectively. Regarding CHF detection, the detection rate of CHF (NYHA III-IV) was 0.9113 while CHF (NYHA I-II) was 0.7312, which shows that the detection rate of CHF with higher severity is higher than that of CHF with lower severity. For the clinical 24 hour data (n=42), the overall sensitivity, specificity and accuracy for AF and CHF were 0.8809, 0.9406 and 0.9108, respectively, using normalized RMSSD.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.21-26
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• 2008

In this paper, we extracted descending slope tracing waves (DSTW) and form factors (FF), and compared the detecting results of premature ventricular contraction (PVC) which were derived from DSTW and FF in order to find an efficient method. The 2nd. derivatives and DSTW were employed to extract correct R-waves from ECG. To evaluate extracting methods, ECGs including PVCs from MIT/BIH database were used.

• Clinical and Experimental Pediatrics
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• v.45 no.9
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• pp.1114-1119
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• 2002

Purpose : The purposes of this study were to determine short- and long-term fractal correlation behavior of heart rates during daily activity in patients with neurocardiogenic syncope. Methods : Twenty five patients with histories of neurocardiogenic syncope episodes were included. Their analogue 24h ambulatory Holter electrocardiograms were analyzed. The tape was digitized and the digitized electrocardiograms were partioned into sections of one hour. Then their RR intervals were measured and 20,000 points of RRI were used. To quantify the fractal correlation behavior, we employed the detrended fluctuation analysis, and short-term($n{\leq}16$, ${\alpha}_1$) and long-term(n>16, ${\alpha}_2$) fractal scaling exponents were calculated. Results : When compared to control, 24-hour average values of ${\alpha}_1$ and all ${\alpha}_1$ values at quarters of each day were significantly higher in patients with syncope. On the contrary, their 24-hour average value of ${\alpha}_2$ and all ${\alpha}_2$ values at quarters of each day were lower in patients with syncope. However, statistical significances were found in 24-hour average value of ${\alpha}_2$ and in ${\alpha}_2$ value at MN-6AM. Conclusion : In the syncope patients with neurocardiogenic syncope, short-term fractal scaling exponents of RR interval was significantly high throughout the day. Therefore, their RR intervals were smoother in the short term scale and had a tendency to continue in the same direction of increase or decrease, which may contribute to persistent decrease in heart rate during a syncopal attack.

• Science of Emotion and Sensibility
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• v.15 no.3
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• pp.345-354
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• 2012

The purpose of this study is finding alternative parameters of the HRV so as to minimize the subjective errors by STAI and BDI, could be have two types of significant correlation levels depending on normalized method. Particularly, the LF/HF presented as the quantitative physiological parameter that can reflect both state-anxiety and trait-anxiety.