Robust Fetal Heart Beat Detection via R-Peak Intervals Distribution

Lin, Chen; Yeh, Hui-Ming; Lo, Men-Tzung; Yeh, Chien-Hung; Wang, Cheng-Yen; Shi, Wenbin; Serafico, Bess Ma. Fabinal; Wang, Chen-Hsu; Juan, Chung‐Hau; Young, Hsu-Wen Vincent; Lin, Yenn‐Jiang

doi:10.1109/tbme.2019.2904014

Cited by 43 publications

(11 citation statements)

References 29 publications

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“…Nonstationarity can significantly compromise the results of complexity analysis especially for the arrhythmias [22]. We identified the QRS complexes by implementing an adaptive threshold, based on the concept of order-statistic filter, which can be effective for wide ranges and variations of heart rate [23]. Then, the detected QRS peaks were visually inspected to avoid automatic misdetections, and the arrhythmic beats, such as atrial premature contractions, and ventricular premature contractions were removed and replaced by the estimated RR using cubic spline interpolation.…”

Section: -H Holter Recording and Data Processingmentioning

confidence: 99%

The Value of Heart Rhythm Complexity in Identifying High-Risk Pulmonary Hypertension Patients

Tang

Hung

et al. 2021

Entropy

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Pulmonary hypertension (PH) is a fatal disease—even with state-of-the-art medical treatment. Non-invasive clinical tools for risk stratification are still lacking. The aim of this study was to investigate the clinical utility of heart rhythm complexity in risk stratification for PH patients. We prospectively enrolled 54 PH patients, including 20 high-risk patients (group A; defined as WHO functional class IV or class III with severely compromised hemodynamics), and 34 low-risk patients (group B). Both linear and non-linear heart rate variability (HRV) variables, including detrended fluctuation analysis (DFA) and multiscale entropy (MSE), were analyzed. In linear and non-linear HRV analysis, low frequency and high frequency ratio, DFAα1, MSE slope 5, scale 5, and area 6–20 were significantly lower in group A. Among all HRV variables, MSE scale 5 (AUC: 0.758) had the best predictive power to discriminate the two groups. In multivariable analysis, MSE scale 5 (p = 0.010) was the only significantly predictor of severe PH in all HRV variables. In conclusion, the patients with severe PH had worse heart rhythm complexity. MSE parameters, especially scale 5, can help to identify high-risk PH patients.

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Section: -H Holter Recording and Data Processingmentioning

confidence: 99%

The Value of Heart Rhythm Complexity in Identifying High-Risk Pulmonary Hypertension Patients

Tang

Hung

et al. 2021

Entropy

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“…The number of articles probing the use of non-linear measures to assess the fHR signals analysis has been growing in the past decade. Non-linear analysis has been successfully applied in the study of fetal heart rate with several research objectives, such as fetal maturation or gestational age (197)(198)(199), fetal gender (182,200), labor stages (201,202), cesarean section (51,203), preterm birth (80,204), impact of nuchal cord on antenatal (205), fHR baseline (206), behavioral state (207,208), IUGR (209)(210)(211)(212)(213), hypoxia (128,137,214,215), fetal distress (216)(217)(218), maternal pathologies (219,220), and signal processing (198,(221)(222)(223)(224). Therefore, it is important that the scientific community is aware of the non-linear methods used depending on the research objective.…”

Section: Discussionmentioning

confidence: 99%

Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review

et al. 2021

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The analysis of fetal heart rate variability has served as a scientific and diagnostic tool to quantify cardiac activity fluctuations, being good indicators of fetal well-being. Many mathematical analyses were proposed to evaluate fetal heart rate variability. We focused on non-linear analysis based on concepts of chaos, fractality, and complexity: entropies, compression, fractal analysis, and wavelets. These methods have been successfully applied in the signal processing phase and increase knowledge about cardiovascular dynamics in healthy and pathological fetuses. This review summarizes those methods and investigates how non-linear measures are related to each paper's research objectives. Of the 388 articles obtained in the PubMed/Medline database and of the 421 articles in the Web of Science database, 270 articles were included in the review after all exclusion criteria were applied. While approximate entropy is the most used method in classification papers, in signal processing, the most used non-linear method was Daubechies wavelets. The top five primary research objectives covered by the selected papers were detection of signal processing, hypoxia, maturation or gestational age, intrauterine growth restriction, and fetal distress. This review shows that non-linear indices can be used to assess numerous prenatal conditions. However, they are not yet applied in clinical practice due to some critical concerns. Some studies show that the combination of several linear and non-linear indices would be ideal for improving the analysis of the fetus's well-being. Future studies should narrow the research question so a meta-analysis could be performed, probing the indices' performance.

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“…Email: {zhouziqun, huangkejie, yueq235, shen hb}@zju.edu.cn. Rate (FHR) by enhancing the fetal R-peak or eliminating the noise components [2], [3]. Most of the existing works, such as the most well-known wavelet transform methods, aim to extract accurate FHR, which may distort the original waveform of FECG signals [4].…”

Section: Morphology Extraction Of Fetal Electrocardiogram By Slow-fast Lstm Networkmentioning

confidence: 99%

Morphology extraction of fetal electrocardiogram by slow-fast LSTM network

Zhou

Huang

Qiu

et al. 2021

Biomedical Signal Processing and Control

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Robust Fetal Heart Beat Detection via R-Peak Intervals Distribution

Cited by 43 publications

References 29 publications

The Value of Heart Rhythm Complexity in Identifying High-Risk Pulmonary Hypertension Patients

The Value of Heart Rhythm Complexity in Identifying High-Risk Pulmonary Hypertension Patients

Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review

Morphology extraction of fetal electrocardiogram by slow-fast LSTM network

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