Ectopic beats detection and correction methods: A review

Dib, Nabil; Reguig, F. Bereksi

doi:10.1016/j.bspc.2015.01.008

Cited by 51 publications

(49 citation statements)

References 82 publications

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“…In this study, TG (including TG/KO) mice exhibited lower values of time‐, frequency‐ and nonlinear‐domain HRV indices (such as SDNN, DC, TIndex and LF), which was in keeping with human reports on patients with higher risk of arrhythmias 3‐28 . The linear interpolation was adopted to replace the ectopic beats before HRV indices calculation to avoid the influence by ectopic beats on HRV measures 29 . The linear interpolation was verified to be the best interpolation method for the frequent ectopic beats compared with the nearest‐neighbour interpolation and the spline interpolation …”

Section: Discussionsupporting

confidence: 63%

Association between heart rate variability indices and features of spontaneous ventricular tachyarrhythmias in mice

Zhao

Nguyen

et al. 2020

Clin Exp Pharma Physio

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Direct evidence is limited for the association between heart rate variability (HRV) indices and ventricular tachyarrhythmias (VTAs). While galectin-3 (Gal-3) is regarded as a causal factor for cardiac remodelling and a biomarker for arrhythmias, its regulation on VTAs and HVR is unknown. Using aged transgenic (TG) mice with cardiac overexpression of β 2 -adrenoceptors and spontaneous VTAs, we studied whether changes in HRV indices correlated with the severity of VTAs, and whether Gal-3 gene knockout (KO) in TG mice might limit VTA. Body-surface ECG was recorded (10-minute period) in 9-to 10-month-old mice of non-transgenic (nTG), TG and TG × Gal-3 knockout (TG/KO). Time-domain, frequency-domain and nonlinear-domain HRV indices were calculated using the R-R intervals extracted from ECG signals and compared with frequency of VTAs. TG and TG/KO mice developed frequent VTAs and showed significant changes in certain time-domain and nonlinear-domain HRV indices relative to nTG mice. The severity of VTAs in TG and TG/KO mice in combination, estimated by VTA counts and arrhythmia score, was significantly correlated with certain timedomain and nonlinear-domain HRV indices. In conclusion, significant changes in HRV indices were evident and correlated with the severity of spontaneous VTAs in TG mice. The frequency of VTA and HRV indices were largely comparable between TG and TG/KO mice. Deletion of Gal-3 in TG mice altered certain HRV indices implying influence by neuronally localized Gal-3 on autonomic nervous activity. K E Y W O R D S cardiomyopathy, galectin-3, heart rate variability, transgenic mouse model, ventricular tachyarrhythmia

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Section: Discussionsupporting

confidence: 63%

Association between heart rate variability indices and features of spontaneous ventricular tachyarrhythmias in mice

Zhao

Nguyen

et al. 2020

Clin Exp Pharma Physio

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“…Although, several studies employed RR data to classify and detect PVC beats [26], approaches that are sufficiently accurate and can execute rapidly for fast realtime PVC detection have proven to be elusive. Knowledge based rules have classified and detected heart beats based on a sliding window technique [38] with positive predictive accuracy and sensitivity values of 86.54 % and 87.27 % respectively for PVCs.…”

Section: Related Workmentioning

confidence: 99%

“…The fact that PVC beats have a QRS pattern wider than Non PVC beats allows identification of these beats relatively easily and counts of RR intervals can be expected to be significantly different [26] [27]. The PVC detection technique was executed in five main steps as demonstrated in the algorithm below.…”

Section: Pvc Detection Techniquementioning

confidence: 99%

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A count data model for heart rate variability forecasting and premature ventricular contraction detection

Allami

Stranieri

Balasubramanian

et al. 2017

SIViP

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“…Unlike the normal beats generated by the sinoatrial node, ectopic beats are generated by additional electrical impulses imposed by other latent pacemakers [ 27 ]. Ectopic beats may cause bias in the reliable measurement of HRV in both the time and frequency domains [ 28 , 29 ], as well as in entropy measurement [ 30 ]. Even the presence of only one ectopic beat can introduce an increase in the high frequency power in HRV of around 10% [ 31 ].…”

Section: Introductionmentioning

confidence: 99%

Suppressing the Influence of Ectopic Beats by Applying a Physical Threshold-Based Sample Entropy

Zhao

Xiong

et al. 2020

Entropy

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Sample entropy (SampEn) is widely used for electrocardiogram (ECG) signal analysis to quantify the inherent complexity or regularity of RR interval time series (i.e., heart rate variability (HRV)), with the hypothesis that RR interval time series in pathological conditions output lower SampEn values. However, ectopic beats can significantly influence the entropy values, resulting in difficulty in distinguishing the pathological situation from normal situations. Although a theoretical operation is to exclude the ectopic intervals during HRV analysis, it is not easy to identify all of them in practice, especially for the dynamic ECG signal. Thus, it is important to suppress the influence of ectopic beats on entropy results, i.e., to improve the robustness and stability of entropy measurement for ectopic beats-inserted RR interval time series. In this study, we introduced a physical threshold-based SampEn method, and tested its ability to suppress the influence of ectopic beats for HRV analysis. An experiment on the PhysioNet/MIT RR Interval Databases showed that the SampEn use physical meaning threshold has better performance not only for different data types (normal sinus rhythm (NSR) or congestive heart failure (CHF) recordings), but also for different types of ectopic beat (atrial beats, ventricular beats or both), indicating that using a physical meaning threshold makes SampEn become more consistent and stable.

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Ectopic beats detection and correction methods: A review

Cited by 51 publications

References 82 publications

Association between heart rate variability indices and features of spontaneous ventricular tachyarrhythmias in mice

Association between heart rate variability indices and features of spontaneous ventricular tachyarrhythmias in mice

A count data model for heart rate variability forecasting and premature ventricular contraction detection

Suppressing the Influence of Ectopic Beats by Applying a Physical Threshold-Based Sample Entropy

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