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Journal of Perinatal Medicine Nov 2015To examine how complex and irregular fetal heart rate (FHR) dynamics differ between fetuses of normal pregnancies and those of pregnancies complicated by maternal anemia...
AIM
To examine how complex and irregular fetal heart rate (FHR) dynamics differ between fetuses of normal pregnancies and those of pregnancies complicated by maternal anemia (MA), and to place this in the context of high-risk pregnancies.
METHODS
Our study population consisted of 97 pregnant women affected by MA, 118 affected by pregnancy-induced hypertension (PIH), 88 affected by gestational diabetes mellitus (GDM), 53 with preterm premature rupture of membranes (pPROM), and 356 normal pregnancies as controls. We calculated approximate entropy (ApEn), sample entropy (SampEn), and correlation dimension (CD) to quantify irregularity and the chaotic dynamics of each FHR time series.
RESULTS
The ApEn in the fetuses of the MA and PIH groups was significantly lower than that of the normal controls (P<0.05). The SampEn was significantly lower in the high-risk groups, except for the pPROM group, than in the normal controls (P<0.05). The CD in the PIH and severe MA groups was significantly lower than that of the normal controls (P<0.05, respectively). In the MA group, the dynamic indices showed a highly significant positive correlation with hemoglobin (Hb) levels (P<0.0001).
CONCLUSION
The decreased complexity and/or irregularity in the FHR from pregnancies with MA may reflect abnormalities in the complex, integrated cardiovascular control. The irregularity and complexity of the FHR increased together with Hb levels in pregnancies with MA. Our data suggest that the integrity of the nervous system in the fetuses compromised by severe MA might result directly in adverse outcomes.
Topics: Adult; Anemia; Case-Control Studies; Diabetes, Gestational; Female; Fetal Membranes, Premature Rupture; Heart Rate, Fetal; Humans; Hypertension, Pregnancy-Induced; Male; Pregnancy; Pregnancy Complications, Hematologic; Pregnancy, High-Risk
PubMed: 25178901
DOI: 10.1515/jpm-2014-0104 -
Acta Paediatrica (Oslo, Norway : 1992) Nov 1993Autonomic and behavioral response to fear stimulation (sudden noise 80 dB) was studied in 12 sleeping infants at ages 8-50 weeks. The aim of the present study was to... (Clinical Trial)
Clinical Trial Comparative Study
Autonomic and behavioral response to fear stimulation (sudden noise 80 dB) was studied in 12 sleeping infants at ages 8-50 weeks. The aim of the present study was to identify a possible passive defense response in infants. The response, which is widespread in birds and mammals, is characterized by apnea and bradycardia with circulatory changes as seen during the forced diving response. Upon stimulation, two respiratory responses were elicited: apnea preceded by irregular respiration or simple irregular respiration. Apnea was elicited in 58% of stimulations at ages 8-16 weeks compared to 14% at 28-50 weeks. The mean duration of apnea decreased from 7.8 s (+/- 1.8 s) at 8-13 weeks to 4.7 s (+/- 1.1 s) at 17-20 weeks. The preceding irregular respiration increased from 5.3 s (+/- 4.4 s) to 10.6 s (+/- 5.4 s) at the same ages. The heart rate response was biphasic and were interpreted as the orienting response. The mean deceleration in relation to apnea was 16% at 8-16 weeks and was reduced to 8% at 28-50 weeks. Infants of smoking mothers were more prone to respond with apnea than infants of non-smoking mothers (73% versus 38%). REM sleep and long postprandial sleep time increased the probability of apnea response (62% versus 38% and 66% versus 35%). The responses seen may be interpreted as expressions of the passive defense response.
Topics: Acoustic Stimulation; Autonomic Nervous System; Female; Heart Rate; Humans; Infant; Male; Movement; Polysomnography; Pregnancy; Prenatal Exposure Delayed Effects; Respiration; Sleep; Sleep Apnea Syndromes; Sleep, REM
PubMed: 8111169
DOI: 10.1111/j.1651-2227.1993.tb12598.x -
The Japanese Journal of Physiology Feb 1997How left ventricular (LV) contractility relates to irregular RR intervals during atrial fibrillation (AF) is still unclear. We investigated the relationship between the...
How left ventricular (LV) contractility relates to irregular RR intervals during atrial fibrillation (AF) is still unclear. We investigated the relationship between the LV contractility (Emax) of individual beats and their preceding RR intervals during AF in isovolumic contractions is excised cross-circulated canine hearts, and additionally in ejecting contractions in in situ canine hearts. Atrial high-frequency electrical stimulation induced AF. We recorded a LV electrocardiogram, volume and pressure, and calculated the Emax of every arrhythmic beat. Multiple linear regression analysis between Emax and the six preceding RR intervals of all arrhythmic beats during 1 min AF showed the preceding RR interval (RR1) and the pre-preceding interval (RR2) to be the predominant predictors of Emax. The Emax-RR1/RR2 scattergram was closely fitted by a linear regression line. We found Emax at RR1/RR2 = 1 on the regression line to be virtually identical with both mean Emax during AF and stable Emax obtained during irregular atrial pacing at the same intervals as the mean RR interval during AF. These results newly indicate that the pressure-interval relationship predominantly characterizes LV irregular beat contractilities and their mean level during AF.
Topics: Animals; Atrial Fibrillation; Blood Pressure; Dogs; Heart Rate; In Vitro Techniques; Myocardial Contraction; Time Factors; Ventricular Dysfunction, Left
PubMed: 9159649
DOI: 10.2170/jjphysiol.47.101 -
Annual International Conference of the... Jul 2017Atrial Fibrillation (AF) is the most common arrhythmia and it is estimated to affect 33.5 million people worldwide. AF is associated with an increased risk of mortality...
Atrial Fibrillation (AF) is the most common arrhythmia and it is estimated to affect 33.5 million people worldwide. AF is associated with an increased risk of mortality and morbidity, such as heart failure and stroke and affects mostly older persons and persons with other conditions (e.g. heart failure and coronary artery disease). In order to prevent such life threatening and life quality reducing conditions it is essential to provide better algorithms, capable of being integrated in low-cost personalized health systems. This paper presents a new algorithm for AF detection, which is based on the analysis of the three physiological characteristics of AF: 1) Irregularity of heart rate and; 2) Absence of P-waves and 3) Presence of fibrillatory waves. Based on these characteristics several features were extracted from 12-lead electrocardiograms (ECG) and selected according to their discrimination ability. The classification between AF and non-AF episodes was performed using a Support Vector Machine (SVM) classification model. Our results show that the identification of the fibrillatory patterns, using the proposed features, extracted from the analysis of 12-lead ECG improves the performance of the algorithm to a sensitivity of 88.5% and specificity 92.9%, when compared to our previous single-channel approach, in the same database.
Topics: Algorithms; Atrial Fibrillation; Electrocardiography; Heart Rate; Humans
PubMed: 29060109
DOI: 10.1109/EMBC.2017.8037065 -
Annual International Conference of the... Jul 2019Entropy quantification algorithms are a prominent tool for the quantification of irregularity in biological signal segments towards the characterization of the...
Entropy quantification algorithms are a prominent tool for the quantification of irregularity in biological signal segments towards the characterization of the physiological state of individuals. This paper investigates the potential of Dispersion Entropy (DisEn) as a non-linear method to quantify the uncertainty of ECG signal segments for different types of heartbeats and the stratification of healthy heartbeats for the potential detection of developing pathologies in individuals. Our results indicate that the DisEn algorithm produces distributions with significant differences for the considered types of heartbeats, with higher DisEn values being more prominent in pathological heartbeats and normal heartbeats preceding them. This suggests that, with further research, DisEn algorithms can be integrated with heartbeat detection and classification algorithms for the improvement of medical prognosis through ECG signal processing.
Topics: Algorithms; Electrocardiography; Entropy; Heart Rate; Humans; Signal Processing, Computer-Assisted
PubMed: 31946352
DOI: 10.1109/EMBC.2019.8856554 -
Physiological Measurement Mar 2023. The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of...
. The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of atrial fibrillation (AF) patients continuously monitored with an implantable cardiac monitor. We will use a mixed model approach to investigate population effect and patient specific effects of heart rate characteristics on AFR, and will correct for the effect of previous ablations, episode duration, and onset date and time.. The f-wave signals, from which AFR is estimated, were extracted using a QRST cancellation process of the AF episodes in a cohort of 99 patients (67% male; 57 ± 12 years) monitored for 9.2(0.2-24.3) months as median(min-max). The AFR from 2453 f-wave signals included in the analysis was estimated using a model-based approach. The association between AFR and heart rate characteristics, prior ablations, and episode-related features were modelled using fixed-effect and mixed-effect modelling approaches.. The mixed-effect models had a better fit to the data than fixed-effect models showing h.c. of determination (2 = 0.49 versus2 = 0.04) when relating the variations of AFR to the heart rate features. However, when correcting for the other factors, the mixed-effect model showed the best fit (2 = 0.04). AFR was found to be significantly affected by previous catheter ablations (< 0.05), episode duration (< 0.05), and irregularity of theinterval series (< 0.05).. Mixed-effect models are more suitable for AFR modelling. AFR was shown to be faster in episodes with longer duration, less organizedintervals and after several ablation procedures.
Topics: Humans; Male; Female; Atrial Fibrillation; Heart Rate; Electrocardiography; Time Factors; Prostheses and Implants
PubMed: 36787645
DOI: 10.1088/1361-6579/acbc08 -
Computers in Biology and Medicine May 2016Screening of atrial fibrillation (AF) for high-risk patients including all patients aged 65 years and older is important for prevention of risk of stroke. Different...
BACKGROUND
Screening of atrial fibrillation (AF) for high-risk patients including all patients aged 65 years and older is important for prevention of risk of stroke. Different technologies such as modified blood pressure monitor, single lead ECG-based finger-probe, and smart phone using plethysmogram signal have been emerging for this purpose. All these technologies use irregularity of heartbeat duration as a feature for AF detection. We have investigated a normalization method of heartbeat duration for improved AF detection.
METHOD
AF is an arrhythmia in which heartbeat duration generally becomes irregularly irregular. From a window of heartbeat duration, we estimate the possible rhythm of the majority of heartbeats and normalize duration of all heartbeats in the window based on the rhythm so that we can measure the irregularity of heartbeats for both AF and non-AF rhythms in the same scale. Irregularity is measured by the entropy of distribution of the normalized duration. Then we classify a window of heartbeats as AF or non-AF by thresholding the measured irregularity. The effect of this normalization is evaluated by comparing AF detection performances using duration with the normalization, without normalization, and with other existing normalizations.
RESULTS
Sensitivity and specificity of AF detection using normalized heartbeat duration were tested on two landmark databases available online and compared with results of other methods (with/without normalization) by receiver operating characteristic (ROC) curves. ROC analysis showed that the normalization was able to improve the performance of AF detection and it was consistent for a wide range of sensitivity and specificity for use of different thresholds. Detection accuracy was also computed for equal rates of sensitivity and specificity for different methods. Using normalized heartbeat duration, we obtained 96.38% accuracy which is more than 4% improvement compared to AF detection without normalization.
CONCLUSIONS
The proposed normalization method was found useful for improving performance and robustness of AF detection. Incorporation of this method in a screening device could be crucial to reduce the risk of AF-related stroke. In general, the incorporation of the rhythm-based normalization in an AF detection method seems important for developing a robust AF screening device.
Topics: Atrial Fibrillation; Heart Rate; Humans
PubMed: 27043858
DOI: 10.1016/j.compbiomed.2016.03.015 -
Cardiology in the Young Mar 2022Approximate Entropy is an extensively enforced metric to evaluate chaotic responses and irregularities of RR intervals sourced from an eletrocardiogram. However, to...
INTRODUCTION
Approximate Entropy is an extensively enforced metric to evaluate chaotic responses and irregularities of RR intervals sourced from an eletrocardiogram. However, to estimate their responses, it has one major problem - the accurate determination of tolerances and embedding dimensions. So, we aimed to overt this potential hazard by calculating numerous alternatives to detect their optimality in malnourished children.
MATERIALS AND METHODS
We evaluated 70 subjects split equally: malnourished children and controls. To estimate autonomic modulation, the heart rate was measured lacking any physical, sensory or pharmacologic stimuli. In the time series attained, Approximate Entropy was computed for tolerance (0.1→0.5 in intervals of 0.1) and embedding dimension (1→5 in intervals of 1) and the statistical significances between the groups by their Cohen's ds and Hedges's gs were totalled.
RESULTS
The uppermost value of statistical significance accomplished for the effect sizes for any of the combinations was -0.2897 (Cohen's ds) and -0.2865 (Hedges's gs). This was achieved with embedding dimension = 5 and tolerance = 0.3.
CONCLUSIONS
Approximate Entropy was able to identify a reduction in chaotic response via malnourished children. The best values of embedding dimension and tolerance of the Approximate Entropy to identify malnourished children were, respectively, embedding dimension = 5 and embedding tolerance = 0.3. Nevertheless, Approximate Entropy is still an unreliable mathematical marker to regulate this.
Topics: Autonomic Nervous System; Child; Entropy; Heart Rate; Humans; Time Factors
PubMed: 34134801
DOI: 10.1017/S1047951121002316 -
Journal of Cardiovascular Magnetic... Dec 2011Stiffening of the arteries results in increased pulse-wave velocity (PWV), the propagation velocity of the blood. Elevated aortic PWV has been shown to correlate with...
PURPOSE
Stiffening of the arteries results in increased pulse-wave velocity (PWV), the propagation velocity of the blood. Elevated aortic PWV has been shown to correlate with aging and atherosclerotic alterations. We extended a previous non-triggered projection-based cardiovascular MR method and demonstrate its feasibility by mapping the PWV of the aortic arch, thoraco-abdominal aorta and iliofemoral arteries in a cohort of healthy adults.
MATERIALS AND METHODS
The proposed method "simultaneously" excites and collects a series of velocity-encoded projections at two arterial segments to estimate the wave-front velocity, which inherently probes the high-frequency component of the dynamic vessel wall modulus in response to oscillatory pressure waves. The regional PWVs were quantified in a small pilot study in healthy subjects (N = 10, age range 23 to 68 yrs) at 3T.
RESULTS
The projection-based method successfully time-resolved regional PWVs for 8-10 cardiac cycles without gating and demonstrated the feasibility of monitoring beat-to-beat changes in PWV resulting from heart rate irregularities. For dual-slice excitation the aliasing was negligible and did not interfere with PWV quantification. The aortic arch and thoracoabdominal aorta PWV were positively correlated with age (p < 0.05), consistent with previous reports. On the other hand, the PWV of the iliofemoral arteries showed decreasing trend with age, which has been associated with the weakening of muscular arteries, a natural aging process.
CONCLUSION
The PWV map of the arterial tree from ascending aorta to femoral arteries may provide additional insight into pathophysiology of vascular aging and atherosclerosis.
Topics: Adult; Aged; Aorta, Abdominal; Aorta, Thoracic; Arteries; Blood Pressure; Feasibility Studies; Femoral Artery; Heart Rate; Humans; Iliac Artery; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Middle Aged; Philadelphia; Pilot Projects; Pulsatile Flow; Reference Values; Regional Blood Flow; Time Factors; Young Adult
PubMed: 22188972
DOI: 10.1186/1532-429X-13-81 -
Sensors (Basel, Switzerland) Nov 2023Smartwatches equipped with automatic atrial fibrillation (AF) detection through electrocardiogram (ECG) recording are increasingly prevalent. We have recently reported...
Smartwatches equipped with automatic atrial fibrillation (AF) detection through electrocardiogram (ECG) recording are increasingly prevalent. We have recently reported the limitations of the Apple Watch (AW) in correctly diagnosing AF. In this study, we aim to apply a data science approach to a large dataset of smartwatch ECGs in order to deliver an improved algorithm. We included 723 patients (579 patients for algorithm development and 144 patients for validation) who underwent ECG recording with an AW and a 12-lead ECG (21% had AF and 24% had no ECG abnormalities). Similar to the existing algorithm, we first screened for AF by detecting irregularities in ventricular intervals. However, as opposed to the existing algorithm, we included all ECGs (not applying quality or heart rate exclusion criteria) but we excluded ECGs in which we identified regular patterns within the irregular rhythms by screening for interval clusters. This "irregularly irregular" approach resulted in a significant improvement in accuracy compared to the existing AW algorithm (sensitivity of 90% versus 83%, specificity of 92% versus 79%, < 0.01). Identifying regularity within irregular rhythms is an accurate yet inclusive method to detect AF using a smartwatch ECG.
Topics: Humans; Atrial Fibrillation; Electrocardiography; Heart Rate; Algorithms
PubMed: 38005669
DOI: 10.3390/s23229283