动态心电图在小儿心律失常与心率变异性诊断中的意义

目的：研究动态心电图（DCG）诊断小儿心律失常及心率变异性（HVR）的临床价值。方法：560 例患者均进行常规心电图和动 态心电图的检查,由两组专业人员分别对心电图（ECG）和动态心电图（DCG）的检查结果进行（评价）,比较两种检查手段的不同 类型的心律失常的诊出率;评价不同类型心律失常的HVR。结果：ECG对各型心律失常的总诊出率为25.00%,对不同类型心率失 常的诊出率分别为5.71%、1.43%、9.29%、6.43%和2.14%;DCG 总诊出率为62.85%,对不同类型心率失常的诊出率分别为 16.43%、6.43%、17.86%、14.29%和7.86%,二者具有统计学差异（P＜0.05）。不同类型的心律失常的HVR不同,其中室性心动过速 和室性期前收缩的各项指标均明显低于其他类型（P＜0.05）。结论：DCG对不同心律失常的诊出率明显高于ECG,并能有效反应 不同类型心率失常的HVR,在小儿心律失常的诊断中具有一定的临床价值。     

Machine Learning Approach to Detect Cardiac Arrhythmias in ECG Signals: A Survey

Cardiac arrhythmia is a condition when the heart rate is irregular either the beat is too slow or too fast. It occurs due to improper electrical impulses that coordinates the heart beats. Sudden cardiac death may occurs due to some dangerous arrhythmias conditions. Hence the main objective of the electrocardiogram (ECG) analysis is to detect the life-threatening arrhythmias accurately for appropriate treatment in order to save life. Since the last decades, several methods were reported for automatic ECG beat classifications. In this work, we present a systematic review of the current state-of-the-art methods used to detect cardiac arrhythmia using on ECG signals. It includes the signal decomposition, feature extraction and machine learning approaches used for automatic detection and decision making process. The articles covers the pre-processing, detection of QRS complex, feature extraction and classification of ECG beats. Based on the past studies, it is understood that the automated approach using computer-aided decision making process is highly required for real-time detection of cardiac arrhythmias. The advantages and limitations of different methods are discussed and also the future scopes is highlighted in the process of effective detection of cardiac arrhythmias. This study could be beneficial for researchers to analyze the existing state-of-art techniques used in detection of arrhythmia conditions.     

A robust method for diagnosis of morphological arrhythmias based on Hermitian model of higher-order statistics

Background  

Electrocardiography (ECG) signal is a primary criterion for medical practitioners to diagnose heart diseases. The development of a reliable, accurate, non-invasive and robust method for arrhythmia detection could assists cardiologists in the study of patients with heart diseases. This paper provides a method for morphological heart arrhythmia detection which might have different shapes in one category and also different morphologies in relation to the patients. The distinctive property of this method in addition to accuracy is the robustness of that, in presence of Gaussian noise, time and amplitude shift.     

Non-Invasive Drosophila ECG Recording by Using Eutectic Gallium-Indium Alloy Electrode: A Feasible Tool for Future Research on the Molecular Mechanisms Involved in Cardiac Arrhythmia

Background

Drosophila heart tube is a feasible model for cardiac physiological research. However, obtaining Drosophila electrocardiograms (ECGs) is difficult, due to the weak signals and limited contact area to apply electrodes. This paper presents a non-invasive Gallium-Indium (GaIn) based recording system for Drosophila ECG measurement, providing the heart rate and heartbeat features to be observed. This novel, high-signal-quality system prolongs the recording time of insect ECGs, and provides a feasible platform for research on the molecular mechanisms involved in cardiovascular diseases.

Methods

In this study, two types of electrode, tungsten needle probes and GaIn electrodes, were used respectively to noiselessly conduct invasive and noninvasive ECG recordings of Drosophila. To further analyze electrode properties, circuit models were established and simulated. By using electromagnetic shielded heart signal acquiring system, consisted of analog amplification and digital filtering, the ECG signals of three phenotypes that have different heart functions were recorded without dissection.

Results and Discussion

The ECG waveforms of different phenotypes of Drosophila recorded invasively and repeatedly with n value (n>5) performed obvious difference in heart rate. In long period ECG recordings, non-invasive method implemented by GaIn electrodes acts relatively stable in both amplitude and period. To analyze GaIn electrode, the correctness of GaIn electrode model established by this paper was validated, presenting accuracy, stability, and reliability.

Conclusions

Noninvasive ECG recording by GaIn electrodes was presented for recording Drosophila pupae ECG signals within a limited contact area and signal strength. Thus, the observation of ECG changes in normal and SERCA-depleted Drosophila over an extended period is feasible. This method prolongs insect survival time while conserving major ECG features, and provides a platform for electrophysiological signal research on the molecular mechanism involved in cardiac arrhythmia, as well as research related to drug screening and development.     

动态心电图与常规心电图诊断冠心病患者心律失常的效果比较

目的:分析冠心病(Coronary heart disease,CHD)心律失常(Arrhythmia)患者诊断中常规心电图(ECG)和动态心电图(DCG)两种诊断方式效果。方法:选取我院收治的CHD患者84例作为研究对象,分别使用ECG和DCG两种方式进行诊断,判断2种方法冠心病检测阳性率、心律失常检出率的情况。结果:动态组检测的阳性率为63.10%(53例),常规组为58.33%(49例),数据差异无统计学意义P0.05;8项心律失常指标中房性/室上性早搏早发、方式传导阻滞等检出率差异无统计学意义,P0.05;其余5项检出率差异显著,P0.05。结论:冠心病心律失常患者的诊断时采用动态心电图在冠心病诊断阳性率和心律失常检出率方面均有一定的优势。     

老年人动态心电图心律失常特点及对阵发性 房颤的诊断

目的:分析65岁以上老年人十二导联动态心电图(12-Holter)心律失常的特点及其对阵发性房颤的诊断价值。方法:①采用回顾性分析的方法,随机选择500例65岁以上老年人的动态心电图进行心律失常情况的统计分析,并同时选择500例小于65岁的心电图作为对照;②另选择500例65岁以上老年人的十二导联普通心电图(ECG)作为对照,对比分析12-Holter与ECG两种方法对老年人阵发性房颤的检出率。结果:①65岁以上老年人动态心电图各种心律失常、ST-T改变的发生率高。而在各类心律失常中房性早搏、室性期前收缩、房性心动过速、房颤发生率较高。②动态心电图对于阵发性房颤的检出率显著高于普通十二导联心电图。结论:①老年人动态心电图检查结果异常率高;②与普通心电图比较,动态心电图诊断老年人阵发性房颤有较高的价值。     

尿素对小鼠体表心电图和心室肌细胞钠离子通道电流的影响

目的：观察尿素对小鼠体表心电图和心室肌细胞钠离子通道电流的影响。方法：使用常规的心电图记录方法和膜片钳实验技术,分别记录小鼠体表心电图和心室肌细胞钠离子通道电流。结果：尿素可以使小鼠心率明显减慢（P〈0．01）,呈浓度依赖性,低、中、高三个剂量组的心率分别由给药前的（612±27、615±23、619±26）b·min^-1下降到给药后的（556±29、469±37、378±48）b·min^-1,并且中、高剂量组发生了不同程度的传导阻滞性心律失常;尿素对小鼠心室肌细胞钠电流有明显的抑制作用（P〈0．05）,钠电流分别由给药前的（8．76±0．91、8．87±1．01、8．77±0．96）nA降低到给药后的（7．32±0．68、5．69±0．64、4．58±0．57）nA,呈浓度依赖性。结论：尿素可以通过抑制心室肌细胞钠电流使小鼠发生传导阻滞性心律失常。     

HEART RATE AND ELECTROCARDIOGRAM CHARACTERISTICS OF A YOUNG CALIFORNIA GRAY WHALE (ESCHRICHTIUS ROBUSTUS)1

Electrocardiogram (ECG) analyses of Holter monitor recordings from a young California gray whale were performed to determine ECG waveform characteristics, evaluate the heart rate pattern for sinus arrhythmia, obtain resting heart rates at known body masses as the whale increased in size, and compare those heart rates with predicted heart rates from allometric equations. The PR and QRS intervals (475 ± 35 msec, 208 ± 24 msec, respectively, n= 20) support the concept (Meijler et al. 1992) that atrioventricular transmission and ventricular excitation times do not increase linearly in very large mammals. A sinus arrhythmia pattern at rest (apneic heart rates of 15–25 beats per min [bpm] and eupneic heart rates of 34–40 bpm) is consistent with a relative eupneic tachycardia and apneic bradycardia during diving activity of whales. The heart rate-body mass measurements (35–24 bpm at body masses of 3,591-8,200 kg) in this study (1) extend the range of allometric heart rate and body mass data in mammals a full order of magnitude, to almost 10,000 kg, (2) support the use of allometric equations (based primarily on mammals <1,000 kg in body mass) in estimating resting heart rates in whales, and (3) demonstrate that previously reported heart rates in large whales are not representative of resting heart rate, probably secondary to circumstances during measurement.     

Arrhythmic Heartbeat Classification Using 2D Convolutional Neural Networks

BackgroundElectrocardiogram (ECG) is a method of recording the electrical activity of the heart and it provides a diagnostic means for heart-related diseases. Arrhythmia is any irregularity of the heartbeat that causes an abnormality in the heart rhythm. Early detection of arrhythmia has great importance to prevent many diseases. Manual analysis of ECG recordings is not practical for quickly identifying arrhythmias that may cause sudden deaths. Hence, many studies have been presented to develop computer-aided-diagnosis (CAD) systems to automatically identify arrhythmias.MethodsThis paper proposes a novel deep learning approach to identify arrhythmias in ECG signals. The proposed approach identifies arrhythmia classes using Convolutional Neural Network (CNN) trained by two-dimensional (2D) ECG beat images. Firstly, ECG signals, which consist of 5 different arrhythmias, are segmented into heartbeats which are transformed into 2D grayscale images. Afterward, the images are used as input for training a new CNN architecture to classify heartbeats.ResultsThe experimental results show that the classification performance of the proposed approach reaches an overall accuracy of 99.7%, sensitivity of 99.7%, and specificity of 99.22% in the classification of five different ECG arrhythmias. Further, the proposed CNN architecture is compared to other popular CNN architectures such as LeNet and ResNet-50 to evaluate the performance of the study.ConclusionsTest results demonstrate that the deep network trained by ECG images provides outstanding classification performance of arrhythmic ECG signals and outperforms similar network architectures. Moreover, the proposed method has lower computational costs compared to existing methods and is more suitable for mobile device-based diagnosis systems as it does not involve any complex preprocessing process. Hence, the proposed approach provides a simple and robust automatic cardiac arrhythmia detection scheme for the classification of ECG arrhythmias.     

Electrocardiographic aspects of skin diving

Electrocardiographic (ECG) aspects of skin diving were monitored by means of continuous ECG recording in a pool 15 m deep. Ten regularly trained divers with different levels of experience divid a minimum of three consecutive times, holding their beath, reaching depths of 6 m, 9 m, and 12 or 15 m. The water temperature was 28 degrees C. During the ascending part of these dives, bradycardia was observed in all skin-divers. Minimal heart rate correlated negatively with the diver's experience (number of dives previously performed). In six divers cardiac arrhythmia was observed. Atrial arrhythmias were sometimes isolated occurrences, but more frequently they were multiple. Ventricular arrhythmias tended to be bigeminal. Apparently, forced expiration through the snorkel when surfacing precipitated these rhythmic disorders.     

基于多尺度快速样本熵与随机森林的心电图分析

目的:探讨基于多尺度快速样本熵与随机森林的心电图分析方法对常见心律失常(房性早搏、室性早搏)的自动诊断的可行性和有效性。方法:利用不同心律失常疾病的心电信号存在复杂性差异的特点,通过多尺度熵计算心电信号在不同尺度下的样本熵值以组成特征向量;利用kd树提高多尺度熵的计算效率,增强算法的实时性。利用训练样本的特征向量构建随机森林分类器,再根据众多决策树的分类结果结合投票原则确定测试样本心律失常疾病的类型。结果:本文提出的心电图分析方法能够有效地识别正常心律、房性早搏(APB)及室性早搏(VPB),平均识别准确率达到91.60%。结论:本文提出的心电图分析方法对常见心律失常(APB,VPB)具有较高的识别准确率及临床实用价值。     

A Powerful Algorithm to aid Cardiac Arrhythmia Diagnosis

Abstract

The Electrocardiogram (ECG), represents the electrical activity of the heart. It is characterised by a number of waves P, QRS, T which are correlated to the status of the heart activity. In this paper, the aim is to present a powerful algorithm to aid cardiac diagnosis. The approach used is based on a determinist method, that of the tree decision. However, the different waves of the ECG signal need to be identified and then measured following a signal to noise enhancement. Signal to noise enhancement is performed by a combiner linear adaptive filter whereas P, QRS, T wave identification and measurement are performed by a derivative approach. Results obtained on simulated and real ECG signals are shown to be highly, satisfactory in the aid of cardiac arrhythmia diagnosis, such as junctionnal escapes, blocks, etc.     

A Powerful Algorithm to aid Cardiac Arrhythmia Diagnosis

The Electrocardiogram (ECG), represents the electrical activity of the heart. It is characterised by a number of waves P, QRS, T which are correlated to the status of the heart activity. In this paper, the aim is to present a powerful algorithm to aid cardiac diagnosis. The approach used is based on a determinist method, that of the tree decision. However, the different waves of the ECG signal need to be identified and then measured following a signal to noise enhancement. Signal to noise enhancement is performed by a combiner linear adaptive filter whereas P, QRS, T wave identification and measurement are performed by a derivative approach. Results obtained on simulated and real ECG signals are shown to be highly, satisfactory in the aid of cardiac arrhythmia diagnosis, such as junctionnal escapes, blocks, etc.     

Effect of potassium channel modulators on toxicity of Cleistanthus collinus

The study was conducted to determine the effects of boiled extract of Cleistanthus collinus on rats by observing ECG changes and electrolyte levels in serum and urine. Influence of minoxidil and glibenclamide on Cleistanthus collinus induced toxicity was determined. ED50 for arrhythmia, changes in contractility and heart rate were recorded using the isolated frog heart. Cleistanthus at low doses caused transient tachycardia and increase in contractility and at high dose caused arrhythmia and cardiac arrest in rat. LD50 was found to be 1690 mg/kg. Minoxidil potentiated cardiac toxicity, whereas glibenclamide did not produce any significant change. High concentration of potassium in Cleistanthus extract hindered comparison of its levels. There was excretion of sodium even in the presence of hyponatraemia. Cleistanthus at low dose caused transient tachycardia and increase in contractility and at high dose caused arrhythmia and cardiac arrest in isolated frog heart. ED50 for arrhythmia was found to be 1406 mg/kg. Acute toxicity was mainly due to depressive cardiac activity of Cleistanthus. It also caused renal failure. Potassium channel modulators did not have important role in acute cardiac toxicity treatment. Probably in chronic toxicity, electrolyte level changes are involved and potassium channel modulators might have a role.     

高龄孕妇孕早期心律失常及转归分析

目的：观察高龄孕妇孕早期ECG异常及心律失常发生特点,记录孕早期房性及室性心律失常的后期转归情况。方法：290例孕妇按照年龄分为35岁以下组,35~39岁组和40~45岁组。行心电图检查,系统分析心电图波形,采集记录异常心电图变化,包括ST段改变、各型心律失常等,记录房性、室性心律失常的好转率及加重率。结果：35~39岁组和40~45岁组心律失常发生率显著高于35岁以下组（P<0.05）;35~39岁组和40~45岁组ST段异常发生率显著高于35岁以下组（P<0.05）;40~45岁组QRS波增宽发生率高于35岁以下组（P<0.05）。35~39岁组和40~45岁组的窦性心动过速、窦性心律不齐和房性早搏发生率显著低于35岁以下组（P<0.05）;40~45岁组阵发性室上速发生率显著高于35岁以下组（P<0.05）,35~39岁组和40~45岁组室性早搏和房颤发生率均显著高于35岁以下组（P<0.05）。40~45岁组的房性心律失常恢复率显著低于35岁以下组（P<0.05）;40~45岁组的房性和室性心律失常加重率显著高于35岁以下组（P<0.05）。35~39岁组的ECG异常组、40~45岁ECG异常组发生率显著高于35岁以下组和35~39岁组的ECG正常组（P<0.05）;35~39岁组及40~45岁的ECG异常组胎儿窘迫发生率显著高于35岁以下组（P<0.05）。结论：高龄与孕早期心律失常发生有正相关,并且高龄因素降低孕期心律失常自行恢复率而升高心律失常恶化发生率,高龄孕妇伴有心电图异常对围生儿状况有不良影响。     

Calsequestrin 2 and arrhythmias

Calsequestrin is the most abundant Ca-binding protein of the specialized endoplasmic reticulum found in muscle, the sarcoplasmic reticulum (SR). Calsequestrin binds Ca with high capacity and low affinity and importantly contributes to the mobilization of Ca during each contraction both in skeletal and cardiac muscle. Surprisingly, mutations in the gene encoding the cardiac isoform of calsequestrin (Casq2) have been associated with an inherited form of ventricular arrhythmia triggered by emotional or physical stress termed catecholaminergic polymorphic ventricular tachycardia (CPVT). Despite normal cardiac contractility and normal resting ECG, CPVT patients present with a high risk of sudden death at a young age. Here, we review recent new insights regarding the role of calsequestrin in genetic and acquired arrhythmia disorders. Mouse models of CPVT have shed light on the pathophysiological mechanism underlying CPVT. Casq2 is not only a Ca-storing protein as initially hypothesized, but it has a far more complex function in Ca handling and regulating SR Ca release channels. The functional importance of Casq2 interactions with other SR proteins and the importance of alterations in Casq2 trafficking are also being investigated. Reports of altered Casq2 trafficking in animal models of acquired heart diseases such as heart failure suggest that Casq2 may contribute to arrhythmia risk beyond genetic forms of Casq2 dysfunction.     

Chlorpromazine: cardiac arrhythmogenicity in the cat

To determine the effect of chlorpromazine on ouabain-induced arrhythmia and death, dial-urethane anesthetized cats were pretreated with chlorpromazine (5, 10, 20, 30, 40, or 60 mg/kg, i.v.) and then administered ouabain (2 microgram/kg/min, i.v.). Blood pressure, heart rate and lead II electrocardiogram (ECG) were monitored. The dosages of ouabain necessary to induce premature ventricular contractions, ventricular tachycardia and death were determined. No significant correlation between the dose of chlorpromazine given and the dose of ouabain required to produce arrhythmia or death was found. These doses of chlorpromazine could, therefore, be considered neither arrhythmogenic nor antiarrhythmic in the ouabain model. To determine whether chlorpromazine produced arrhythmia in the dial-urethane anesthetized cat model, the drug was infused at a rate of 1 mg/kg/min, i.v. Chlorpromazine produced arrhythmia at 185 +/- 4.3 minutes and death via cardiovascular collapse at 128 +/- 4.7 minutes. Bilateral adrenal vein ligation, employed to eliminate the influence of adrenal catecholamines, decreased the dosage of chlorpromazine necessary to produce arrhythmia and death to 67.8 +/- 17.7 and 84.7 +/- 15.7 mg/kg, respectively. Thus, adrenal catecholamines did not appear to contribute to chlorpromazine-induced arrhythmia, although the procedure of bilateral adrenal vein ligation appeared to be deleterious in combination with chlorpromazine. In all experiments, chlorpromazine depressed blood pressure without producing the reflex tachycardia normally seen with hypotension. This suggests that the drug may be interfering with the baroreceptor reflex arc. As chlorpromazine modifies the autonomic parameters of blood pressure, heart rate, and cardiac electrophysiology, sudden unexplained death in patients managed with this agent may be due to drug-induced arrhythmia.     

Time of night effects on heart rate variation in normal neonates

Circadian patterns have been observed in infants as early as the first few postnatal days. We hypothesized that, in each sleep-waking state, heart rate variation in several distinct frequency bands would show consistent variations across a night in newborn infants. Twelve-hour night-time recordings of EEG, ECG, EOG, digastric EMG, respiratory movements, and CO2 were obtained from 25 normal full-term infants at 2-7 days postnatal age. The extents of three types of heart rate variation were determined for all epochs identified as quiet sleep, rapid eye movement (REM) sleep, and waking during each 4-hr period of the night. In particular states, the extent of all three types of heart rate variation decreased from the evening (7-11pm) to the late night (11pm-3am). Heart rate variation at the respiratory frequency showed such a time-of-night effect in quiet sleep only, resulting in a significant sleep state effect on respiratory sinus arrhythmia during the evening that disappeared later in the night. Previous studies have indicated that respiratory sinus arrhythmia is enhanced during quiet sleep, relative to other states, after 3 mo of age; the present findings suggest that the tendency for enhancement during quiet sleep is present even in the neonate, although this tendency is only expressed during the evening. Results indicate that time-of-night effects on heart rate variation are not constant across physiological states in neonates, and heart rate variation during the waking state is particularly unresponsive to these time-of-night influences.     

Long Term ECG Recording with Hotter Monitoring in Clinically Healthy Horses

The electrocardiogram of 9 horses was continuously recorded for 24 h with Holter monitoring to examine the variations in heart rate and rhythm during daily routine procedures and at night. Three horses had transient sinus bradycardia, and 3 had periods of sinus tachycardia. Heart blocks were detected in 3 horses, and all horses had periods of sinus arrhythmia. These changes in the heart rate and rhythm were apparently caused by variations in autonomic nervous system tone and they are probably “normal” findings in resting, undisturbed horses. Ventricular premature depolarisations were not observed in any horse, but some single supraventricular premature contractions were detected. There was preliminary evidence that in order to register the real resting heart rate and rhythm of a horse the ECG should be recorded over a long period, and also at night and without the presence of the investigator.     

三个品系小型猪正常心电图的比较

目的建立清醒状态记录小型猪心电图的方法,并对3个品系小型猪6个导联心电图进行分析比较。方法选用4月龄广西巴马猪7头、5月龄五指山小型猪6头、中国农大小型猪10头,清醒状态下吊床保定,测定Ⅰ、Ⅱ、Ⅲ、aVR、aVL和aVF6个导联的心电图。结果3个品系小型猪心电图的波形与人相似,心率较快,在3个品系之间差别不明显,存在偶发性窦性心率不齐。广西巴马猪、五指山小型猪和中国农大小型猪的P-R间期分别介于0．08—0．10s、0．08—0．11s和0．08—0．11s;QRS波群分别介于0．04—0．06s,0．04—0．07s和0．04～0．05s。3个品系小型猪均有清晰的S-T段,偏移小于1mm。结论本研究获得了3个品系小型猪清醒状态时的心电图基本数据,经比较,3个品系之间无明显差异。