The Neonatal QRS Complex and Its Association with Left Ventricular Mass

To evaluate QRS complex features during the first month of life and the association with echocardiographic measurements of left ventricular mass in neonates. Prospective cohort study of neonates with electrocardiography (ECG) and echocardiography performed during the first month of life. Left ventricular mass index (LVMI) was determined by echocardiography and the correlation with electrocardiographic markers of LVMI outliers (≥ 98th percentile) were analyzed. We included 17,450 neonates (52% boys; median age at examination 11 days) and found an increase in median QRS duration and LVMI during the first month of life (54 vs. 56 ms and 24.7 vs. 28.6 g/m2 at days 0-4 and 25-30, respectively; both p < 0.001). All investigated ECG features (QRS duration, QRS area in V1/V6, maximum amplitudes of S-V1/R-V6, and the Sokolow-Lyon voltage product) showed no to low correlation with LVMI, resulting in low sensitivities (0-9.0%), but high specificities (97.2-98.1%), and area under the curve values close to the identity line (0.49-0.61) for identifying LVMI outliers. Adjustment of outlier definition for LVMI and threshold for QRS features had no significant effect on sensitivity. We present reference values for QRS complex features and their association with LVMI in neonates from a large, unselected, population-based cohort. The QRS complex gradually evolved during the first month of life but had a low correlation with LVMI. Our results indicate a poor diagnostic value of using ECG features to identify LVMI outliers in neonates.Trial Registry Copenhagen Baby Heart, NCT02753348, https://clinicaltri-als.gov/ct2/show/NCT02753348?cond=Copenhagen+Baby+Heart&draw=2&rank=1 , deidentified individual participant data will not be made available.

The role of QRS complex prolongation in predicting severe toxicity in single-xenobiotic overdose

OBJECTIVE

The QRS complex duration is commonly used to prognosticate severity, predict outcomes, and indicate treatment in overdose. However, literature to support this practice is mixed in tricyclic antidepressant overdoses and absent in non-tricyclic antidepressant overdoses. Our objective was to assess the validity of QRS complex duration as a prognostic marker in overdose.

METHODS

This was a secondary analysis of cases reported to the Toxicology Investigators Consortium between January 1, 2010, and December 31, 2022. Cases were assessed to determine the six xenobiotics most associated with QRS complex prolongation. All cases involving these six xenobiotics, regardless of QRS complex duration, constituted the study cohort. Inclusion criteria were cases of patients older than 12 years old with single-xenobiotic exposures. Clinical outcomes evaluated were seizure, ventricular dysrhythmia, metabolic acidosis, and death.

RESULTS

Of 94,939 total cases, diphenhydramine, amitriptyline, bupropion, quetiapine, nortriptyline, and cocaine were most associated with QRS complex prolongation. Inclusion criteria were met by 4,655 cases of exposure to these xenobiotics. QRS complex prolongation was associated with increased odds ratio of seizure in all included xenobiotics, of ventricular dysrhythmia in all included xenobiotics except nortriptyline, and of metabolic acidosis or death in all included xenobiotics except nortriptyline and quetiapine. A normal QRS complex duration had a negative predictive value of greater than or equal to 93.0 percent of developing metabolic acidosis and 98.0 percent of developing a ventricular dysrhythmia or death from the xenobiotics studied.

DISCUSSION

This study demonstrates that patients with QRS complex prolongation from all six xenobiotics studied had an increased prevalence and odds of developing severe outcomes. Furthermore, patients who did not develop QRS complex prolongation were unlikely to develop a ventricular dysrhythmia, metabolic acidosis, or death. These findings were noted in six xenobiotics that mechanistically can cause QRS complex prolongation through sodium channel or gap junction inhibition.

CONCLUSION

Identification of patients at risk for severe outcomes after overdose can be aided by measuring the QRS complex duration. If prospectively validated, these outcomes have implications on risk stratification, disposition level of care, and appropriateness of treatments.

QTc interval measurement in patients with right bundle branch block: A practical method

BACKGROUND AND AIM

Prolonging the QT interval in the right bundle branch block (RBBB) can create challenges for electrophysiologists in estimating repolarization time and eliminating the effect of depolarization changes on QT interval. In this study, we aimed to develop a practice formula to eliminate the effect of depolarization changes on QT interval in patients with RBBB.

METHODS

This prospective study evaluated accidentally induced RBBB in patients undergoing electrophysiological study. Two expert electrophysiologists recorded the ECG parameters, including QRS duration, QT interval, and cycle length, in the patients. The formula was developed based on QT interval differences (with and without RBBB) and its proportion to QRS. Additionally, the Bazzet, Rautaharju, and Hodge formulas were used to evaluate QTc.

RESULTS

We evaluated 96 patients in this study. The mean QT interval without RBBB was 369.39 ± 37.38, reaching 404.22 ± 39.23 after inducing RBBB. ΔQT was calculated as 34.83 ± 17.61, and the ratio of ΔQT/QRS with RBBB was almost 23%. Our formula is: (QT_{with RBBB}  - 23% × QRS). Subtraction of 25% instead of 23% seems more straightforward and practical. Our formula could also predict the QTc interval in RBBB based on the Bazzet, Rautaharju, and Hodge formulas.

CONCLUSION

Previous formulas for QT correction were hard to apply in the clinical setting or were not specified for RBBB. Our new formula allows a rapid and practical method for QT correction in RBBB in clinical practice.

Characterization of rheumatic heart disease from electrocardiogram recordings

Objective. Rheumatic Heart Disease (RHD) is one of the highly prevalent heart diseases in developing countries that can affect the pericardium, myocardium, or endocardium. Rheumatic endocarditis is a common RHD variant that gradually deteriorates the normal function of the heart valves. RHD can be diagnosed using standard echocardiography or listened to as a heart murmur using a stethoscope. The electrocardiogram (ECG), on the other hand, is critical in the study and identification of heart rhythms and abnormalities. The effectiveness of ECG to identify distinguishing signs of rheumatic heart problems, however, has not been adequately examined. This study addressed the possible use of ECG recordings for the characterization of problems of the heart in RHD patients.Approach. To this end, an extensive ECG dataset was collected from patients suffering from RHD (PwRHD), and healthy control subjects (HC). Bandpass filtering was used at the preprocessing stage. Each data was then standardized by removing its mean and dividing by its standard deviation. Delineation of the onsets and offsets of waves was performed using KIT-IBT open ECG MATLAB toolbox. PR interval, QRS duration, RR intervals, QT intervals, and QTc intervals were computed for each heartbeat. The median values of the temporal parameters were used to eliminate possible outliers due to missed ECG waves. The data were clustered in different age groups and sex. Another categorization was done based on the time duration since the first RHD diagnosis.Main results. In 47.2% of the cases, a PR elongation was observed, and in 26.4% of the cases, the QRS duration was elongated. QTc was elongated in 44.3% of the cases. It was also observed that 62.2% of the cases had bradycardia.Significance. The end product of this research can lead to new medical devices and services that can screen RHD based on ECG which could somehow assist in the detection and diagnosis of the disease in low-resource settings and alleviate the burden of the disease.

Algorithm for Mobile Platform-Based Real-Time QRS Detection

Recent advancements in smart, wearable technologies have allowed the detection of various medical conditions. In particular, continuous collection and real-time analysis of electrocardiogram data have enabled the early identification of pathologic cardiac rhythms. Various algorithms to assess cardiac rhythms have been developed, but these utilize excessive computational power. Therefore, adoption to mobile platforms requires more computationally efficient algorithms that do not sacrifice correctness. This study presents a modified QRS detection algorithm, the AccYouRate Modified Pan-Tompkins (AMPT), which is a simplified version of the well-established Pan-Tompkins algorithm. Using archived ECG data from a variety of publicly available datasets, relative to the Pan-Tompkins, the AMPT algorithm demonstrated improved computational efficiency by 5-20×, while also universally enhancing correctness, both of which favor translation to a mobile platform for continuous, real-time QRS detection.

Non-Standard Electrode Placement Strategies for ECG Signal Acquisition

BACKGROUND

Wearable technologies for monitoring cardiovascular parameters, including electrocardiography (ECG) and impedance cardiography (ICG), propose a challenging research subject. The expectancy for wearable devices to be unobtrusive and miniaturized sets a goal to develop smarter devices and better methods for signal acquisition, processing, and decision-making.

METHODS

In this work, non-standard electrode placement configurations (EPC) on the thoracic area and single arm were experimented for ECG signal acquisition. The locations were selected for joint acquisition of ECG and ICG, targeted to suitability for integrating into wearable devices. The methodology for comparing the detected signals of ECG was developed, presented, and applied to determine the R, S, and T waves and RR interval. An algorithm was proposed to distinguish the R waves in the case of large T waves.

RESULTS

Results show the feasibility of using non-standard EPCs, manifesting in recognizable signal waveforms with reasonable quality for post-processing. A considerably lower median sensitivity of R wave was verified (27.3%) compared with T wave (49%) and S wave (44.9%) throughout the used data. The proposed algorithm for distinguishing R wave from large T wave shows satisfactory results.

CONCLUSIONS

The most suitable non-standard locations for ECG monitoring in conjunction with ICG were determined and proposed.

QRS micro-fragmentation as a mortality predictor

AIMS

Fragmented QRS complex with visible notching on standard 12-lead electrocardiogram (ECG) is understood to represent depolarization abnormalities and to signify risk of cardiac events. Depolarization abnormalities with similar prognostic implications likely exist beyond visual recognition but no technology is presently suitable for quantification of such invisible ECG abnormalities. We present such a technology.

METHODS AND RESULTS

A signal processing method projects all ECG leads of the QRS complex into optimized three perpendicular dimensions, reconstructs the ECG back from this three-dimensional projection, and quantifies the difference (QRS 'micro'-fragmentation, QRS-μf) between the original and reconstructed signals. QRS 'micro'-fragmentation was assessed in three different populations: cardiac patients with automatic implantable cardioverter-defibrillators, cardiac patients with severe abnormalities, and general public. The predictive value of QRS-μf for mortality was investigated both univariably and in multivariable comparisons with other risk factors including visible QRS 'macro'-fragmentation, QRS-Mf. The analysis was made in a total of 7779 subjects of whom 504 have not survived the first 5 years of follow-up. In all three populations, QRS-μf was strongly predictive of survival (P < 0.001 univariably, and P < 0.001 to P = 0.024 in multivariable regression analyses). A similar strong association with outcome was found when dichotomizing QRS-μf prospectively at 3.5%. When QRS-μf was used in multivariable analyses, QRS-Mf and QRS duration lost their predictive value.

CONCLUSION

In three populations with different clinical characteristics, QRS-μf was a powerful mortality risk factor independent of several previously established risk indices. Electrophysiologic abnormalities that contribute to increased QRS-μf values are likely responsible for the predictive power of visible QRS-Mf.

QRS complex detection using stationary wavelet transform and adaptive thresholding

Purpose- Electrocardiogram (ECG) signal is a record of the electrical activity of the heart and contains important clinical data about cardiovascular-related misfunctioning. The goal of the present work is to develop an improved QRS detection algorithm for the detection of heart abnormalities. Methods- In this present work stationary wavelet transforms (SWT) based method has been proposed for precise detection of QRS complex with 'sym2' mother wavelet. The stationary wavelet transform is a systematic mathematical tool to decompose the signal without downsampling using scale analysis and provides high detection of QRS complex and accurate localization of signal components. In the proposed method four level of decomposition is applied and the initial thresholding value is computed by the maximum amplitude of scale one at level four in SWT coefficients without the zero-crossing amplitude detection method. The multi-layered dynamic thresholding method has been applied to detect the true R-peak values and locate the QRS complex in the ECG signal. Results- For evaluation of results, the presented methodology is assessed on MIT-BIH, QTDB, and Noise stress test databases. In MIT-BIH, the sensitivity = 99.88%, positive predictivity = 99.93%, accuracy = 99.80% and detection error rate = 0.18% is achieved. In NSTD database, sensitivity = 97.46%, positive predictivity = 94.20%, accuracy = 91.95% and detection error rate = 8.47% and in QTDB, sensitivity = 99.95%, positive predictivity = 99.90%, accuracy = 99.71% and detection error rate = 0.16% is executed. Conclusion- In the presented proposed methodology, the computation complexity is low and exhibits a simple technique rather than an empirical approach. The proposed technique corroborates the performance for the detection of QRS complex with improved accuracy.

An Exploratory Study on Vectorcardiographic Identification of the Site of Origin of Focally Induced Premature Depolarizations in Horses, Part II: The Ventricles

In human cardiology, the anatomical origin of ventricular premature depolarizations (VPDs) is determined by the characteristics of a 12-lead electrocardiogram (ECG). Former studies in horses had contradictory results regarding the diagnostic value of the 12-lead ECG and vectorcardiography (VCG), which results were attributed to the different cardiac conduction system in this species. The objective of this study was to determine if the anatomical origin of pacing-induced VPDs could be differentiated in horses based upon VCG characteristics. A 12-lead ECG was recorded in seven horses under general anesthesia while right and left ventricular endomyocardial pacing was performed (800−1000 ms cycle length) at the apex, mid and high septum and mid and high free wall, and at the right ventricular outflow tract. Catheter positioning was guided by 3D electro-anatomical mapping and echocardiography. A median complex, obtained from four consecutive complexes, was calculated for each pacing location and sinus rhythm. The VCG was calculated from the 12-lead ECG-derived median complexes using custom-made algorithms and was used to determine the initial and maximum electrical axes of the QRS complex. An ANOVA for spherical data was used to test if VCGs between each paced location and between pacing and sinus rhythm were significantly (p < 0.05) different. The model included the radius, azimuth and elevation of each electrical axis. Pacing induced significantly different initial and maximum electrical axes between different locations and between pacing and sinus rhythm. The current results suggest that VCG is a useful technique to identify the anatomical origin of ventricular ectopy in horses.

Deep Learning Techniques in the Classification of ECG Signals Using R-Peak Detection Based on the PTB-XL Dataset

Deep Neural Networks (DNNs) are state-of-the-art machine learning algorithms, the application of which in electrocardiographic signals is gaining importance. So far, limited studies or optimizations using DNN can be found using ECG databases. To explore and achieve effective ECG recognition, this paper presents a convolutional neural network to perform the encoding of a single QRS complex with the addition of entropy-based features. This study aims to determine what combination of signal information provides the best result for classification purposes. The analyzed information included the raw ECG signal, entropy-based features computed from raw ECG signals, extracted QRS complexes, and entropy-based features computed from extracted QRS complexes. The tests were based on the classification of 2, 5, and 20 classes of heart diseases. The research was carried out on the data contained in a PTB-XL database. An innovative method of extracting QRS complexes based on the aggregation of results from established algorithms for multi-lead signals using the k-mean method, at the same time, was presented. The obtained results prove that adding entropy-based features and extracted QRS complexes to the raw signal is beneficial. Raw signals with entropy-based features but without extracted QRS complexes performed much worse.

Retrospective evaluation of notched and fragmented QRS complex in dogs with naturally occurring myxomatous mitral valve disease

Myxomatous mitral valve disease (MMVD) is the most common cardiac disease in dogs. The association of QRS notching (nQRS) or fragmentation (fQRS) with disease severity is currently unknown. The study objective was to assess the prevalence of nQRS and fQRS in dogs with MMVD and its severity according to ACVIM classification and to compare the results with a group of healthy dogs. This retrospective cross-sectional study included 34 healthy control dogs and 155 dogs with spontaneous MMVD (42% of dogs in class B1, 23% in class B2 and 35% in class C). fQRS was defined as nQRS complexes in two contiguous leads in the frontal plane (leads I and aVL) and (II, III or aVF). A one-way ANOVA with Bonferroni post-hoc test was used to assess the differences in continuous data between control and MMVD groups. Of the MMVD group, 58% showed nQRS in at least one lead and 27% presented fQRS. There was no difference between the number of leads with a nQRS and disease severity (p = 0.75) nor did the number of leads with a nQRS correlate with left atrial size (r = 0.48; p = 0.5). The number of dogs with fQRS did not differ among classes of MMVD (p = 0.21). nQRS and fQRS were more prevalent in dogs with MMVD compared to control dogs (p < 0.01). This study did not identify any relationship between the number of leads with a nQRS and disease severity. However, dogs with MMVD had a higher prevalence of nQRS and fQRS compared to control group.

Left bundle branch pacing shortened the QRS duration of a right bundle branch block

Left bundle branch pacing (LBBP) has recently emerged as a novel physiological pacing technique with a paced morphology of a pseudoright bundle branch block (RBBB). We herein present a 63-year-old man with a high-degree atrioventricular block and complete RBBB, whose intrinsic QRS duration and terminal R' wave duration in V1 were significantly shortened after LBBP and further shortened with the increase in output.

An enhanced T-wave delineation method using phasor transform in the electrocardiogram

Accurate detection of key components plays a vital role in determining cardiovascular diseases in the ECG. In this method, we propose an enhanced T-wave delineation method using the phasor transform. Discrete Wavelet Transform (DWT) and median filters were used to suppress the high-frequency noise and baseline drift during pre-processing. The phasor transform was used to detect and locate the delineation points before and after the T-wave. The proposed method was tested on the QTDB for R-peak, T-peak, and T_offdetection. It achieved both sensitivity (Se%) and positive predictivity (+P%) values of 100 for R-peak detection. In T-peak detection, method shows Se % = 99.46 and +P % = 99.54, respectively. This method has reported Se% = 99.34 and +P% = 99.48 for T_offdetection in the ECG. The achieved results show that the method can be used for cardiac arrhythmia detection related to the morphology of T-wave.

IoT-enabled cloud-based real-time remote ECG monitoring system

Statistical reports all around the world have deemed cardiovascular diseases (CVDs) as the largest contributor to the death count. The electrocardiogram (ECG) is a widely accepted technology employed for investigation of CVDs of the person. The proposed solution deals with an efficient internet of things (IoT) enabled real-time ECG monitoring system using cloud computing technologies. The article presents a cloud-centric solution to provide remote monitoring of CVD. Sensed ECG data are transmitted to S3 bucket provided by Amazon web service (AWS) through a mobile gateway. AWS cloud uses HTTP and MQTT servers to provide data visualisation, quick response and long-live connection to device and user. Bluetooth low energy (BLE 4.0) is used as a communication protocol for low-power data transmission between device and mobile gateway. The proposed system is implemented with filtering algorithms to ignore distractions, environmental noise and motion artefacts. It offers an analysis of ECG signals to detect various parameters such as heartbeat, PQRST wave and QRS complex intervals along with respiration rate. The proposed system prototype has been tested and validated for reliable ECG monitoring remotely in real-time.

A novel and lightweight P, QRS, and T peaks detector using adaptive thresholding and template waveform

Accurate detection of key components in an electrocardiogram (ECG) plays a vital role in identifying cardiovascular diseases. In this work, we proposed a novel and lightweight P, QRS, and T peaks detector using adaptive thresholding and template waveform. In the first stage, we proposed a QRS complex detector, which utilises a novel adaptive thresholding process followed by threshold initialisation. Moreover, false positive QRS complexes were removed using the kurtosis coefficient computation. In the second stage, the ECG segment from the S wave point to the Q wave point was extracted for clustering. The template waveform was generated from the cluster members using the ensemble average method, interpolation, and resampling. Next, a novel conditional thresholding process was used to calculate the threshold values based on the template waveform morphology for P and T peaks detection. Finally, the min-max functions were used to detect the P and T peaks. The proposed technique was applied to the MIT-BIH arrhythmia database (MIT-AD) and the QT database for QRS detection and validation. Sensitivity (Se%) values of 99.81 and 99.90 and positive predictivity (+P%) values of 99.85 and 99.94 were obtained for the MIT-AD and QT database for QRS complex detection, respectively. Further, we found that Se% = 96.50 and +P% = 96.08 for the P peak detection, Se% = 100 and +P% = 100 for the R peak detection, and Se% = 99.54 and +P% = 99.68 for the T peak detection when using the manually annotated QT database. The proposed technique exhibits low computational complexity and can be implemented on low-cost hardware, since it is based on simple decision rules rather than a heuristic approach.

The specification of zebrafish (Danio rerio) heart electrocardiogram index characteristic responses to different types of pollutants

Water quality was highly affected by common pollutants. Metals, pesticides and small molecules are ubiquitous pollutants. Advancement in engineering technology (computer-based monitoring systems) increased the efficiency of quantifying toxicity of different chemicals in an organism. The cardiovascular system reflects internal and external stress of an organism, and electrocardiogram (ECG) data reliably measure external stress. As ECG data can accurately reflect the physiological conditions of organisms, and zebrafish (Danio rerio) are considered to be good models for cardiovascular research, it is hypothesized that ECG parameters of zebrafish could indicate the toxicity of water-borne chemicals. To achieve this, we treated zebrafish with different concentrations of target chemicals (CuSO₄, C₁₀H₁₉O₆PS₂ and NH₄Cl) for 48 h and ECG data were measured. P-wave, R-wave, T-wave, PR-interval, QRS-complex and QT-interval data were the focus of this study. The results of self-organizing maps and Pearson correlation analysis indicate that the QRS-complex can be used as an indicator for CuSO₄ stress. The QT-interval could be used to assess the C₁₀H₁₉O₆PS₂ stress. The QT-interval and P-wave can be used to evaluate the NH₄Cl stress. Responses of zebrafish ECG parameters were identical with other vertebrate model, and were specific to toxicant types. It is proved that zebrafish heart ECG index could be used as a potential indicator in early detection of environmental stress.

A robust ECG denoising technique using variable frequency complex demodulation

BACKGROUND AND OBJECTIVE

Electrocardiogram (ECG) is widely used for the detection and diagnosis of cardiac arrhythmias such as atrial fibrillation. Most of the computer-based automatic cardiac abnormality detection algorithms require accurate identification of ECG components such as QRS complexes in order to provide a reliable result. However, ECGs are often contaminated by noise and artifacts, especially if they are obtained using wearable sensors, therefore, identification of accurate QRS complexes often becomes challenging. Most of the existing denoising methods were validated using simulated noise added to a clean ECG signal and they did not consider authentically noisy ECG signals. Moreover, many of them are model-dependent and sampling-frequency dependent and require a large amount of computational time.

METHODS

This paper presents a novel ECG denoising technique using the variable frequency complex demodulation (VFCDM) algorithm, which considers noises from a variety of sources. We used the sub-band decomposition of the noise-contaminated ECG signals using VFCDM to remove the noise components so that better-quality ECGs could be reconstructed. An adaptive automated masking is proposed in order to preserve the QRS complexes while removing the unnecessary noise components. Finally, the ECG was reconstructed using a dynamic reconstruction rule based on automatic identification of the severity of the noise contamination. The ECG signal quality was further improved by removing baseline drift and smoothing via adaptive mean filtering.

RESULTS

Evaluation results on the standard MIT-BIH Arrhythmia database suggest that the proposed denoising technique provides superior denoising performance compared to studies in the literature. Moreover, the proposed method was validated using real-life noise sources collected from the noise stress test database (NSTDB) and data from an armband ECG device which contains significant muscle artifacts. Results from both the wearable armband ECG data and NSTDB data suggest that the proposed denoising method provides significantly better performance in terms of accurate QRS complex detection and signal to noise ratio (SNR) improvement when compared to some of the recent existing denoising algorithms.

CONCLUSIONS

The detailed qualitative and quantitative analysis demonstrated that the proposed denoising method has been robust in filtering varieties of noises present in the ECG. The QRS detection performance of the denoised armband ECG signals indicates that the proposed denoising method has the potential to increase the amount of usable armband ECG data, thus, the armband device with the proposed denoising method could be used for long term monitoring of atrial fibrillation.

Prognostic value of initial QRS analysis in anterior STEMI: Correlation with left ventricular systolic dysfunction, serum biomarkers, and cardiac outcomes

BACKGROUND

The presence of pathologic Q waves on admission electrocardiogram (ECG) in patients with anterior ST-elevated myocardial infarction (STEMI) has been related to adverse cardiac outcomes. Our study evaluates the prognostic value of QRS complex and Q waves in patients with STEMI undergoing percutaneous coronary intervention.

METHODS

We prospectively analyzed the specific characteristics of QRS complex and pathologic Q waves on admission and on discharge ECG in 144 patients hospitalized for anterior STEMI. We correlated these findings with the development of left ventricular systolic dysfunction (LVSD), appearance of heart failure (HF) or death during follow-up, and levels of several biomarkers obtained 6 months after the index event.

RESULTS

Multivariate logistic regression analysis showed that QRS width (odds ratios [OR] 1.05, p = .001) on admission ECG and the sum of Q-wave depth (OR 1.06, p = .002) on discharge ECG were independent predictors of LVSD development. Moreover, QRS width on admission ECG was related to an increased risk of HF or death (OR 1.03, p = .026). Regarding biomarkers, QRS width on admission ECG revealed a statistically significant relationship with the levels of NT-pro-BNP at 6 months (0.29, p = .004); the sum of Q-wave depth (0.27, p = .012) and width (0.25, p = .021) on admission ECG was related to the higher levels of hs-cTnI; the sum of the voltages in precordial leads both on admission ECG (-0.26, p = .011) and discharge ECG (0.24, p = .046) was related to the lower levels of parathormone.

CONCLUSIONS

Assessment of QRS complex width and pathologic Q waves on admission and discharge ECGs aids in predicting long-term prognosis in patients with STEMI.

The phenomenon of concealed conduction in a case of His bundle pacing (HBP)

The phenomenon of concealed conduction in His bundle pacing (HBP) has rarely been reported. We report here a patient who had 2: 1 atrioventricular block and complete left bundle branch block was used because of HBP. The patient developed continuous right bundle branch block after the operation. After excluding mechanical damage, we speculate that the mechanism of right bundle branch block in this case was due to concealed conduction.

Electrocardiographic changes associated with epilepsy beyond heart rate and their utilization in future seizure detection and forecasting methods

The ability to assess seizure risk may help provide timely warnings and more personalized treatment plans for people with epilepsy (PWE). ECG changes are commonly observed in epilepsy which make ECG a promising candidate to monitor seizure risk. Most ECG research in this domain has focused on heart rate-related changes. However, several studies have identified a range of other peri-ictal ECG parameter changes that may potentially prove useful for seizure detection and forecasting. Here, we offer a systematic review of ECG changes in epilepsy outside of heart rate. We performed the systematic literature review according to PRISMA guidelines using key words related to ECG, SUDEP and epilepsy. We identified and screened 502 abstracts, read 110 full papers, and included 24 papers in the final review. Our results suggest that PWE may be more prone to cardiac conduction abnormalities than healthy controls. During interictal periods, PWE were more likely to have abnormal QTc intervals, ST segment abnormalities, elevated T Waves, early repolarization (ER), increased P Wave dispersion and PR intervals when compared to controls. Apart from these baseline abnormalities, changes during the pre-ictal and ictal states have been reported, with arrhythmias, QTc prolongation and ST segment changes being the most common. A better understanding of these state-dependent changes may afford less-cumbersome and less-stigmatizing epilepsy monitoring tools in the future.

Nonspecific intraventricular conduction delay is associated with future occurrence of atrial fibrillation in patients with structurally normal heart

BACKGROUND

We aimed to elucidate the long-term prognosis of nonspecific intraventricular conduction delay (NIVCD) in patients with structurally normal heart.

METHODS

We included 107,838 patients (age, 52.1 ± 15.5 years; men, 46.8%) who underwent electrocardiography in outpatient clinics or medical checkup (unmatched cohort). NIVCD was defined as QRS duration ≥110 ms without meeting the criteria for bundle branch block. Patients with structurally normal heart and sinus rhythm were assigned to the NIVCD and normal QRS groups according to propensity score with matching variables of age, sex, hypertension, and diabetes (matched cohort 1), and additional PR interval (matched cohort 2). Baseline characteristics, electrocardiographic parameters, and clinical outcomes were compared in the unmatched cohort and the matched cohort.

RESULTS

In the unmatched cohort, the frequencies of male sex and preexisting atrial fibrillation were significantly higher in the NIVCD group than in the normal QRS group. In matched cohort 1 (n = 690), the NIVCD group exhibited significant slower sinus rate and longer PR interval than the normal QRS group. In matched cohort 2 (n = 598), the cumulative incidence of atrial fibrillation was significantly higher in the NIVCD group than in the normal QRS group during a follow-up period of 8.8 ± 2.9 years. NIVCD significantly increased the risk for AF (hazard ratio, 2.571; 95% confidence interval, 1.074-6.156; p = 0.034).

CONCLUSIONS

It is suggested that NIVCD may be associated with future occurrence of atrial fibrillation in patients with structurally normal heart and sinus rhythm.

The Association of Metabolic Syndrome and Its Components with Electrocardiogram Parameters and Abnormalities Among an Iranian Rural Population: The Fasa PERSIAN Cohort Study

BACKGROUND

Metabolic syndrome (MetS) as a set of cardiac risk factors and its growing prevalence is one of the major concerns in different societies. In this study, we aimed to investigate the relationship between Mets and electrocardiogram (ECG) parameters and abnormalities as indicators for subclinical cardiovascular diseases (CVD).

METHODS

In this sub-analysis study, we used the data from Fasa PERSIAN Cohort Study which includes subjects age 35-70 years. Subjects with available ECG data included in the study (n=7002) and subjects with missing data on MetS components and non-sinus rhythm ECG were excluded (n=44). The MetS definition based on the Adult Treatment Panel (ATP) III guidelines and also a 12-lead ECG was obtained from all participants.

RESULTS

Our study population (n=6958) showed a mean age of 48.60±9.34 years and also 1656 (24.2%) subjects had MetS. Except for P duration, PR interval and S amplitude in men and P amplitude, S amplitude, Sokolow-Lyon Index, and QT interval in women, other ECG parameters differ significantly between subjects with and without Mets (P<0.05). Also among ECG abnormalities, prolonged P duration (≥120ms), QRS duration (≥100ms), and QTc interval (>450ms in male, >470ms in female) had a significant association with MetS in the total population. Waist circumferences (WC) showed the most count of significant relationship with ECG parameters in both genders. In males, WC more than ATP cut-points had significant associations with prolonged P and QRS duration, and also blood pressure (BP) had significant associations with prolonged P and QRS durations and QTc interval. In females, the MetS component except triglyceride had at least a significant relationship with prolonged P and/or QRS duration.

CONCLUSION

MetS and its component especially WC and BP were associated with ECG parameters and abnormalities. These associations with ECG as a marker of subclinical CVD showed the importance of MetS and each component in our population to monitor in the further longitudinal studies.

Immediate clinical outcomes of left bundle branch area pacing vs conventional right ventricular pacing

BACKGROUND

Left bundle branch area pacing (LBBaP) is a new physiological pacing strategy that produces comparable clinical effects to His bundle pacing (HBP).

OBJECTIVE

The purpose of this study was to investigate the immediate clinical outcomes of LBBaP vs RVP.

METHODS AND RESULTS

From April 2018 to September 2018, we included 44 patients under continuous pacemaker implantation. Patients were randomly divided into the LBBaP group and conventional RVP group. Compared to the RVP group, the LBBaP group displayed significantly increased operative (90.10 ± 19.68 minutes vs 61.57 ± 6.62 minutes, P < .001) and X-ray exposure times (15.55 ± 5.62 minutes vs 4.67 ± 2.06 minutes, P < .001). The lead threshold of the LBBaP group was increased (0.68 ± 0.20 mV vs 0.51 ± 0.0 mV, P = .001), while the R-wave amplitude and ventricular impedance did not significantly differ between the two groups. The conventional RVP procedure significantly widened the QRS complex (93.62 ± 8.28 ms vs 135.19 ± 12.21 ms, P = .001), whereas the LBBaP had no effect on QRS complex (130.13 ± 43.30 ms vs 112.63 ± 12.14 ms, P = .904). Furthermore, the LBBaP procedure significantly narrowed the QRS complex in patients with left bundle branch block (LBBB) (168.43 ± 38.870 ms vs 119.86 ± 6.69 ms, P = .019).

CONCLUSION

LBBaP is a new physiological, safe and effective pacing procedure with a high overall success rate. Compared to conventional RVP, LBBaP can correct LBBB, thereby improving cardiac electrical dyssynchrony.

VERB: VFCDM-Based Electrocardiogram Reconstruction and Beat Detection Algorithm

We have developed a novel method to accurately detect QRS complex peaks using the variable frequency complex demodulation (VFCDM) method. The approach's novelty stems from reconstructing an ECG signal using only the frequency components associated with the QRS waveforms by VFCDM decomposition. After signal reconstruction, both top and bottom sides of the signal are used for peak detection, after which we compare locations of the peaks detected from both sides to ensure false peaks are minimized. Finally, we impose position-dependent adaptive thresholds to remove any remaining false peaks from the prior step. We applied the proposed method to the widely benchmarked MIT-BIH arrhythmia dataset, and obtained among the best results compared to many of the recently published methods. Our approach resulted in 99.94% sensitivity, 99.95% positive predictive value and a 0.11% detection error rate. Three other datasets-the MIMIC III database, University of Massachusetts atrial fibrillation data, and SCUBA diving in salt water ECG data-were used to further test the robustness of our proposed algorithm. For all these three datasets, our method retained consistently higher accuracy when compared to the BioSig Matlab toolbox, which is publicly available and known to be reliable for ECG peak detection.

Efficient Fiducial Point Detection of ECG QRS Complex Based on Polygonal Approximation

Electrocardiogram signal analysis is based on detecting a fiducial point consisting of the onset, offset, and peak of each waveform. The accurate diagnosis of arrhythmias depends on the accuracy of fiducial point detection. Detecting the onset and offset fiducial points is ambiguous because the feature values are similar to those of the surrounding sample. To improve the accuracy of this paper's fiducial point detection, the signal is represented by a small number of vertices through a curvature-based vertex selection technique using polygonal approximation. The proposed method minimizes the number of candidate samples for fiducial point detection and emphasizes these sample's feature values to enable reliable detection. It is also sensitive to the morphological changes of various QRS complexes by generating an accumulated signal of the amplitude change rate between vertices as an auxiliary signal. To verify the superiority of the proposed algorithm, error distribution is measured through comparison with the QT-DB annotation provided by Physionet. The mean and standard deviation of the onset and the offset were stable as - 4.02 ± 7.99 ms and - 5.45 ± 8.04 ms, respectively. The results show that proposed method using small number of vertices is acceptable in practical applications. We also confirmed that the proposed method is effective through the clustering of the QRS complex. Experiments on the arrhythmia data of MIT-BIH ADB confirmed reliable fiducial point detection results for various types of QRS complexes.

A different effect of obesity on ECG in premenopausal and postmenopausal women

Both obesity and menopause are significant cardiovascular risk factors. In postmenopausal women the protective effect of estrogens is reduced and menopause is frequently associated with occurrence of other significant cardiovascular factors including obesity. This study was focused on evaluating the effect of obesity on the QRS complex in pre- and postmenopausal women. We present results of analysis of 199 electrocardiograms of pre- and postmenopausal women analyzed in relation to the body mass index within normal limits (BMI 20 to 24.9 kg/m²) and obesity (BMI > 30 kg/m²), respectively. Obesity in premenopausal women and menopause significantly affected both the electrical axis (EA) and maximum QRS spatial vector magnitude (QRSmax). The highest QRSmax and electrical axis values were observed in premenopausal lean women, and they were significantly higher as than in the premenopausal obese women, postmenopausal lean and obese women (QRSmax: 1.66 ± 0.4 mV, 1.17 ± 0.35 mV, 1.4 ± 0.46 mV, and 1.35 ± 0.39 mV, resp.). (EA: 56.4 ± 18.0°, 38.22 ± 18.38°, 45.82 ± 18.63°, and 36.75 ± 17.51°). The differences between obese premenopausal women, lean and obese postmenopausal women were not statistically significant. These differences were reflected in 12-lead ECG amplitude. The presence of additional cardiovascular risk factors did not affect the ECG parameters. Obesity significantly affected QRS complex in premenopausal women. This effect was comparable with the effect of menopause. Because all QRS complex changes were within normal limits, these results suggest that ECG evaluation in women should go beyond traditional diagnostic categories and consider the relationship between ECG changes and two cardiovascular risk factors - obesity and menopause.

Toxic responses of zebrafish (Danio rerio) to thallium and deltamethrin characterized in the electrocardiogram

The electrocardiogram (ECG) has been widely used to objectively address the physical condition as an index of stress. Though a numerous accounts of investigations on aquatic organisms' ECGs have been made, differentiation of ECG parameters in responding to specific toxic chemicals has not been extensively studied. In this research, it is hypothesized that zebrafish (Danio rerio) ECG parameters would differently respond to different types of pollutants, a heavy metal, thallium (Tl, 0.10 and 13.00 μg/L) and an organic chemical, deltamethrin (DM, 0.52 and 2.00 μg/L). Based on the SOM training and statistical analyses, QRS complex could be specified as an indicator of Tl stress, while QT interval might be used to evaluate DM stress. Pearson correlation analysis indicated that QRS complex and QT interval were significantly associated with Tl stress (r = 0.854, p = 0.0002) and DM stress (r = 0.792, p = 0.001), respectively. QRS complex and QT interval had the highest R², the minimum of SSE and the lowest AIC value in Tl and DM treatments, respectively. Bases on the current experimental results and previous reports, QRS complex and QT interval could be considered as a specific indicator of Tl and DM disturbances in the environment, respectively.

[Leadless endocardial ultrasound based left ventricular stimulation : WISE CRT System: alternative to conventional methods]

There are still several limitations in delivering cardiac resynchronisation therapy (CRT). After 6 months, 20-40% of patients fail to have clinical benefit due to various reasons. Endocardial stimulation rather than conventional epicardial pacing has been shown to be more physiological, improves electrical stimulation of the left ventricle (LV), has less dispersion of electrical activity and results in better resynchronisation. The WiSE™ CRT System ("Wireless stimulation endocardial system"; EBR Systems, Sunnyvale, CA, USA) provides an option for wireless, LV endocardial pacing triggered by a conventional right ventricular pacing spike from a co-implant. The feasibility of the WiSE™ CRT System has been successfully demonstrated in a population of failed cardiac resynchronisation patients with either failed implantation of a conventional system, nonresponse to conventional therapy or upgrade from pacemaker or defibrillator, where a conventional system was not an option. The WiSE™ CRT System is an innovative technology with promising safety, performance and preliminary efficacy.

Design of high performance QRS complex detector for wearable healthcare devices using biorthogonal spline wavelet transform

A high performance QRS complex detector applicable for wearable healthcare devices is proposed in the present work. Since, higher SNR results in better detection accuracy and lesser number of coefficients reduces the hardware resources as well as power dissipation during on chip implementation. Biorthogonal spline wavelet transform is chosen for the proposed detector as it has high signal to noise ratio (SNR) and uses only four coefficients for decomposition. In the proposed approach, a Biorthogonal wavelet filter bank with fourth level decomposition is first used to separate the different frequency components and then a fourth level wavelet filter bank is used to get the denoised electrocardiogram (ECG) signals. Wavelet filter bank outputs are multiplied and soft threshold method is applied to get the QRS complex peaks by the QRS complex peak detector block. Add and shift multiplier used in the earlier designs has been replaced by a Booth multiplier in our approach to achieve the higher performance. Booth multiplier and QRS complex peak detector blocks have been designed for low hardware complexity, high performance and accurate detection of the QRS complex peaks. Time interval between the consecutive QRS peaks is calculated using the R-R peak time calculator block and the heart rate (HR) by the HR calculator block. Heart Rate Variability (HRV) and arrhythmia are detected based on these heart rate calculations. Proposed design has been tested for its robustness on multiple datasets (namely, MIT-BIH arrhythmia, MIT-BIH noise stress test, and MIT-BIH atrial fibrillation databases). Sensitivity of 99.31%, positive predictivity of 99.19% and the Detection Error Rate (DER) of 1.49% shown by the proposed design makes it preferable for QRS complex detectors used in wearable healthcare devices.

Feature extraction of ECG signal

This paper deals with new approaches to analyse electrocardiogram (ECG) signals for extracting useful diagnostic features. Initially, elimination of different types of noise is carried out using maximal overlap discrete wavelet transform (MODWT) and universal thresholding. Next, R-peak fiducial points are detected from these noise free ECG signals using discrete wavelet transform along with thresholding. Then, extraction of other features, viz., Q waves, S waves, P waves, T waves, P wave onset and offset points, T wave onset and offset points, QRS onset and offset points are identified using some rule based algorithms. Eventually, other important features are computed using the above extracted features. The software developed for this purpose has been validated by extensive testing of ECG signals acquired from the MIT-BIH database. The resulting signals and tabular results illustrate the performance of the proposed method. The sensitivity, predictivity and error of beat detection are 99.98%, 99.97% and 0.05%, respectively. The performance of the proposed beat detection method is compared to other existing techniques, which shows that the proposed method is superior to other methods.

A combined low-frequency electromagnetic and fluidic stimulation for a controlled drug release from superparamagnetic calcium phosphate nanoparticles: potential application for cardiovascular diseases

Alternative drug delivery approaches to treat cardiovascular diseases are currently under intense investigation. In this domain, the possibility to target the heart and tailor the amount of drug dose by using a combination of magnetic nanoparticles (NPs) and electromagnetic devices is a fascinating approach. Here, an electromagnetic device based on Helmholtz coils was generated for the application of low-frequency magnetic stimulations to manage drug release from biocompatible superparamagnetic Fe-hydroxyapatite NPs (FeHAs). Integrated with a fluidic circuit mimicking the flow of the cardiovascular environment, the device was efficient to trigger the release of a model drug (ibuprofen) from FeHAs as a function of the applied frequencies. Furthermore, the biological effects on the cardiac system of the identified electromagnetic exposure were assessed in vitro and in vivo by acute stimulation of isolated adult cardiomyocytes and in an animal model. The cardio-compatibility of FeHAs was also assessed in vitro and in an animal model. No alterations of cardiac electrophysiological properties were observed in both cases, providing the evidence that the combination of low-frequency magnetic stimulations and FeHAs might represent a promising strategy for controlled drug delivery to the failing heart.

Summation and Cancellation Effects on QRS and ST-Segment Changes Induced by Simultaneous Regional Myocardial Ischemia

Simultaneous ischemia in two myocardial regions is a potentially lethal clinical condition often unrecognized whose corresponding electrocardiographic (ECG) patterns have not yet been characterized. Thus, this study aimed to determine the QRS complex and ST-segment changes induced by concurrent ischemia in different myocardial regions elicited by combined double occlusion of the three main coronary arteries. For this purpose, 12 swine were randomized to combination of 5-min single and double coronary artery occlusion: Group 1: left Circumflex (LCX) and right (RCA) coronary arteries (n = 4); Group 2: left anterior descending artery (LAD) and LCX (n = 4) and; Group 3: LAD and RCA (n = 4). QRS duration and ST-segment displacement were measured in 15-lead ECG. As compared with single occlusion, double LCX+RCA blockade induced significant QRS widening of about 40 ms in nearly all ECG leads and magnification of the ST-segment depression in leads V1-V3 (maximal 228% in lead V3, p < 0.05). In contrast, LAD+LCX or LAD+RCA did not induce significant QRS widening and markedly attenuated the ST-segment elevation in precordial leads (maximal attenuation of 60% in lead V3 in LAD+LCX and 86% in lead V5 in LAD+RCA, p < 0.05). ST-segment elevation in leads V7-V9 was a specific sign of single LCX occlusion. In conclusion, concurrent infero-lateral ischemia was associated with a marked summation effect of the ECG changes previously elicited by each single ischemic region. By contrast, a cancellation effect on ST-segment changes with no QRS widening was observed when the left anterior descending artery was involved.

The variability of automated QRS duration measurement

Aims

Previous studies have demonstrated substantial variability in manual assessment of QRS complex duration (QRSd). Disagreements in QRSd measurements were also found in several automated algorithms tested on digitized electrocardiogram (ECG) recordings. The aim of our study was to investigate the variability of automated QRSd measurements performed by two commercially available electrocardiographs.

Methods and Results

Two GE MAC 5000 (GE-1 and GE-2) electrocardiographs and two Mortara ELI 350 (Mortara-1 and Mortara-2) electrocardiographs were used in the study. Participants for the study were recruited from patients hospitalized in the department of cardiology of a university hospital. Participants underwent up to four recording sessions within a single day with a different electrocardiograph at each session when two to four immediately successive ECG recordings were undertaken. In 76 patients, 683 ECGs were recorded; the mean QRSd was 109.0 ± 26.1 ms. The QRSd difference ≥10 ms between the first and second intra-session ECG was found in 7, 3, 20, and 14% of ECG pairs for GE-1, GE-2, Mortara-1, and Mortara-2, respectively. No inter-session difference in QRSd was found within both manufacturers. In individual patients, Mortara calculated the mean QRSd to be longer by 7.3 ms (95% CI: 6.2-8.5 ms, P < 0.0001) with a 2.1-times (95% CI: 1.9-2.4) greater standard deviation of the mean QRSd (7.1 vs. 3.3 ms, P < 0.001).

Conclusion

Electrocardiographs from two manufacturers measured QRSd values with a systematic difference and a significantly different level of precision. This may have important clinical implications in selection of suitable candidates for cardiac resynchronization therapy.

General Approach to a Wide QRS Complex

Wide QRS complex is present when the normal activation pattern is modified by various mechanisms and clinical conditions. Correct interpretation is crucial for appropriate decision making. When approaching an electrocardiogram (ECG) with wide complex tachycardia, one must differentiate between ventricular tachycardia and supraventricular tachycardia conducted with aberrancy. ECG criteria are used and algorithms developed to aid in differential diagnosis. They are based on finding ECG signs of ventriculoatrial dissociation and QRS morphologies inconsistent with classic bundle branch block. The conditions able to modify structurally the normal activation of the heart may alter spontaneous ventricular activation during supraventricular tachycardia, creating differential diagnosis problems.

Human ventricular activation sequence and the simulation of the electrocardiographic QRS complex and its variability in healthy and intraventricular block conditions

Aims

To investigate how variability in activation sequence and passive conduction properties translates into clinical variability in QRS biomarkers, and gain novel physiological knowledge on the information contained in the human QRS complex.

Methods and results

Multiscale bidomain simulations using a detailed heart-torso human anatomical model are performed to investigate the impact of activation sequence characteristics on clinical QRS biomarkers. Activation sequences are built and validated against experimentally-derived ex vivo and in vivo human activation data. R-peak amplitude exhibits the largest variability in terms of QRS morphology, due to its simultaneous modulation by activation sequence speed, myocardial intracellular and extracellular conductivities, and propagation through the human torso. QRS width, however, is regulated by endocardial activation speed and intracellular myocardial conductivities, whereas QR intervals are only affected by the endocardial activation profile. Variability in the apico-basal location of activation sites on the anterior and posterior left ventricular wall is associated with S-wave progression in limb and precordial leads, respectively, and occasional notched QRS complexes in precordial derivations. Variability in the number of early activation sites successfully reproduces pathological abnormalities of the human conduction system in the QRS complex.

Conclusion

Variability in activation sequence and passive conduction properties captures and explains a large part of the clinical variability observed in the human QRS complex. Our physiological insights allow for a deeper interpretation of human QRS biomarkers in terms of QRS morphology and location of early endocardial activation sites. This might be used to attain a better patient-specific knowledge of activation sequence from routine body-surface electrocardiograms.

Left Ventricular Hypertrophy by the Surface ECG

Left ventricular hypertrophy (LVH) is defined as an increase in left ventricular mass (LVM) associated with structural changes of myocardium. The increase in LVM and associated changes are associated with changes in depolarization and repolarization, manifested as a variety of altered QRS and T patterns. Increased QRS voltage has been considered to be a specific ECG finding in LVH, and ECG criteria based on this increased QRS voltage are generally recommended. These ECG changes are also predictive of adverse cardiovascular outcomes. However, it must also be noted that the majority of patients with increased LVM do not have increased QRS voltage. While this is often considered a limitation of ECG in LVH diagnosis, the authors of this minireview consider it more likely that the electrical effects, represented in the altered ECG, and the increased LVM are independent effects, associated by virtue of their common relationship with an underlying pathologic state. This revised view challenges cardiologists and electrocardiologists to explore the interrelationships between electrical, biochemical, and mechanical alterations of myocardial remodeling seen with heart disease, to advance our understanding of this process and its effects, including the evolution of the ECG changes known as "LVH".

Wenckebach pattern in right bundle branch block - benign or not?

A Mobitz type I block (Wenckebach phenomenon) with narrow QRS complex is almost always due to a lesion in the AV node. In a type I block with wide QRS complex (>0.12sec), the block can be in the His-Purkinje system in 60-70% of the cases. Even though the progressive PR prolongation with every conducted beat suggests Wenckebach phenomenon, one needs to pay attention to the accompanying QRS complex. In the setting of persistent right bundle branch block, axis change of subsequent conducted beat before an unconducted p suggests alternating fascicular block, giving clue to unreliable infra-Hisian conduction; and in the setting of symptoms, a pacemaker should be implanted. Infra-Hisian Wenckebach block is rare with only sparse literature reports. The present case report adds to these, suggesting that wide QRS with Wenckebach block on surface ECG may indicate infra-Hisian conduction abnormalities.

Real time QRS complex detection using DFA and regular grammar

Background

The sequence of Q, R, and S peaks (QRS) complex detection is a crucial procedure in electrocardiogram (ECG) processing and analysis. We propose a novel approach for QRS complex detection based on the deterministic finite automata with the addition of some constraints. This paper confirms that regular grammar is useful for extracting QRS complexes and interpreting normalized ECG signals. A QRS is assimilated to a pair of adjacent peaks which meet certain criteria of standard deviation and duration.

Results

The proposed method was applied on several kinds of ECG signals issued from the standard MIT-BIH arrhythmia database. A total of 48 signals were used. For an input signal, several parameters were determined, such as QRS durations, RR distances, and the peaks’ amplitudes. σRR and σQRS parameters were added to quantify the regularity of RR distances and QRS durations, respectively. The sensitivity rate of the suggested method was 99.74% and the specificity rate was 99.86%. Moreover, the sensitivity and the specificity rates variations according to the Signal-to-Noise Ratio were performed.

Conclusions

Regular grammar with the addition of some constraints and deterministic automata proved functional for ECG signals diagnosis. Compared to statistical methods, the use of grammar provides satisfactory and competitive results and indices that are comparable to or even better than those cited in the literature.

Smart Helmet: Wearable Multichannel ECG and EEG

Modern wearable technologies have enabled continuous recording of vital signs, however, for activities such as cycling, motor-racing, or military engagement, a helmet with embedded sensors would provide maximum convenience and the opportunity to monitor simultaneously both the vital signs and the electroencephalogram (EEG). To this end, we investigate the feasibility of recording the electrocardiogram (ECG), respiration, and EEG from face-lead locations, by embedding multiple electrodes within a standard helmet. The electrode positions are at the lower jaw, mastoids, and forehead, while for validation purposes a respiration belt around the thorax and a reference ECG from the chest serve as ground truth to assess the performance. The within-helmet EEG is verified by exposing the subjects to periodic visual and auditory stimuli and screening the recordings for the steady-state evoked potentials in response to these stimuli. Cycling and walking are chosen as real-world activities to illustrate how to deal with the so-induced irregular motion artifacts, which contaminate the recordings. We also propose a multivariate R-peak detection algorithm suitable for such noisy environments. Recordings in real-world scenarios support a proof of concept of the feasibility of recording vital signs and EEG from the proposed smart helmet.

PKPD modelling of PR and QRS intervals in conscious dogs using standard safety pharmacology data

INTRODUCTION

Pharmacokinetic-pharmacodynamic (PKPD) modelling can improve safety assessment, but few PKPD models describing drug-induced QRS and PR prolongations have been published. This investigation aims to develop and evaluate PKPD models for describing QRS and PR effects in routine safety studies.

METHODS

Exposure and telemetry data from safety pharmacology studies in conscious beagle dogs were acquired. Mixed effects baseline and PK-QRS/PR models were developed for the anti-arrhythmic compounds AZD1305, flecainide, quinidine and verapamil and the anti-muscarinic compounds AZD8683 and AZD9164. RR interval correction and circadian rhythms were investigated for predicting baseline variability. Individual PK predictions were used to drive the pharmacological effects evaluating linear and non-linear direct and effect compartment models.

RESULTS

Conduction slowing induced by the tested anti-arrhythmics was direct and proportional at low exposures, whilst time delays and non-linear effects were evident for the tested anti-muscarinics. AZD1305, flecainide and quinidine induced QRS widening with 4.2, 10 and 5.6% μM(-1) unbound drug. AZD1305 and flecainide also prolonged PR with 13.5 and 11.5% μM(-1). PR prolongations induced by the anti-muscarinics and verapamil were best described by Emax models with maximal effects ranging from 55 to 95%. RR interval correction and circadian rhythm improved PR but not QRS modelling. However, circadian rhythm had minor impact on estimated drug effects.

DISCUSSION

Baseline and drug-induced effects on QRS and PR intervals can be effectively described with PKPD models using routine data, providing quantitative safety information to support drug discovery and development.

Robust detection of premature ventricular contractions using sparse signal decomposition and temporal features

An automated noise-robust premature ventricular contraction (PVC) detection method is proposed based on the sparse signal decomposition, temporal features, and decision rules. In this Letter, the authors exploit sparse expansion of electrocardiogram (ECG) signals on mixed dictionaries for simultaneously enhancing the QRS complex and reducing the influence of tall P and T waves, baseline wanders, and muscle artefacts. They further investigate a set of ten generalised temporal features combined with decision-rule-based detection algorithm for discriminating PVC beats from non-PVC beats. The accuracy and robustness of the proposed method is evaluated using 47 ECG recordings from the MIT/BIH arrhythmia database. Evaluation results show that the proposed method achieves an average sensitivity of 89.69%, and specificity 99.63%. Results further show that the proposed decision-rule-based algorithm with ten generalised features can accurately detect different patterns of PVC beats (uniform and multiform, couplets, triplets, and ventricular tachycardia) in presence of other normal and abnormal heartbeats.

New electrocardiographic criteria to differentiate acute pericarditis and myocardial infarction

OBJECTIVE

Transmural myocardial ischemia induces changes in QRS complex and QT interval duration but, theoretically, these changes might not occur in acute pericarditis provided that the injury is not transmural. This study aims to assess whether QRS and QT duration permit distinguishing acute pericarditis and acute transmural myocardial ischemia.

METHODS

Clinical records and 12-lead electrocardiogram (ECG) at ×2 magnification were analyzed in 79 patients with acute pericarditis and in 71 with acute ST-segment elevation myocardial infarction (STEMI).

RESULTS

ECG leads with maximal ST-segment elevation showed longer QRS complex and shorter QT interval than leads with isoelectric ST segment in patients with STEMI (QRS: 85.9 ± 13.6 ms vs 81.3 ± 10.4 ms, P = .01; QT: 364.4 ± 38.6 vs 370.9 ± 37.0 ms, P = .04), but not in patients with pericarditis (QRS: 81.5 ± 12.5 ms vs 81.0 ± 7.9 ms, P = .69; QT: 347.9 ± 32.4 vs 347.3 ± 35.1 ms, P = .83). QT interval dispersion among the 12-ECG leads was greater in STEMI than in patients with pericarditis (69.8 ± 20.8 ms vs 50.6 ± 20.2 ms, P <.001). The diagnostic yield of classical ECG criteria (PR deviation and J point level in lead aVR and the number of leads with ST-segment elevation, ST-segment depression, and PR-segment depression) increased significantly (P = .012) when the QRS and QT changes were added to the diagnostic algorithm.

CONCLUSIONS

Patients with acute STEMI, but not those with acute pericarditis, show prolongation of QRS complex and shortening of QT interval in ECG leads with ST-segment elevation. These new findings may improve the differential diagnostic yield of the classical ECG criteria.

Assessment of reproducibility--automated and digital caliper ECG measurement in the Framingham Heart Study

BACKGROUND

Digitized electrocardiography permits the rapid, automated quantification of electrocardiograms (ECGs) for analysis. Community- and population-based studies have increasingly integrated such data. Assessing the reproducibility of automated ECG measures with manual measures is a critical step in preparation for using automated measures for research purposes. We recently established an ECG repository of digitally recorded ECGs for the Framingham Heart Study and we sought to assess the reproducibility of automated and manual measures.

METHODS

We selected 185 digitally recorded ECGs from routine visits of Framingham Heart Study participants spanning from 1986 to 2012. We selected the following ECG measures for their relevance to clinical and epidemiologic research: P wave duration, P wave amplitude, and PR interval in lead II; QRS duration and R wave amplitude in lead V6; and QT interval in lead V5. We obtained automated values for each waveform, and used a digital caliper for manual measurements. Digital caliper measurements were repeated in a subset (n=81) of the samples for intrarater assessment.

RESULTS

We calculated the intraclass correlation coefficient (ICC) values for the interrater and intrarater assessments. P wave duration had the lowest interrater ICC (r=0.46) and lowest intrarater ICC (r=0.57). R wave amplitude had the highest interrater and intrarater ICC (r=0.98) indicating excellent reproducibility. The remaining measures had interrater and intrarater ICCs of r≥0.81.

CONCLUSIONS

The interrater reproducibility findings for P wave amplitude, PR interval, QT interval, QRS duration, and R wave amplitude were excellent. In contrast, the reproducibility of P wave duration was more modest. These findings indicate high reproducibility of most automated and manual ECG measurements.

Mechanical dyssynchrony precedes QRS widening in ATP-sensitive K⁺ channel-deficient dilated cardiomyopathy

Background

Contractile discordance exacerbates cardiac dysfunction, aggravating heart failure outcome. Dissecting the genesis of mechanical dyssynchrony would enable an early diagnosis before advanced disease.

Methods and Results

High‐resolution speckle‐tracking echocardiography was applied in a knockout murine surrogate of adult‐onset human cardiomyopathy caused by mutations in cardioprotective ATP‐sensitive K⁺ (K_ATP) channels. Preceding the established criteria of cardiac dyssynchrony, multiparametric speckle‐based strain resolved nascent erosion of dysfunctional regions within cardiomyopathic ventricles of the K_ATP channel–null mutant exposed to hemodynamic stress. Not observed in wild‐type counterparts, intraventricular disparity in wall motion, validated by the degree, direction, and delay of myocardial speckle patterns, unmasked the disease substrate from asymptomatic to overt heart failure. Mechanical dyssynchrony preceded widening of the QRS complex and exercise intolerance and progressed into global myocardial discoordination and decompensated cardiac pump function, precipitating a low output syndrome.

Conclusions

The present study, with the use of high‐resolution imaging, prospectively resolved the origin and extent of intraventricular motion disparity in a K_ATP channel–knockout model of dilated cardiomyopathy. Mechanical dyssynchrony established as an early marker of cardiomyopathic disease offers novel insight into the pathodynamics of dyssynchronous heart failure.

QRS analysis using wavelet transformation for the prediction of response to cardiac resynchronization therapy: a prospective pilot study

BACKGROUND

Wider QRS and left bundle branch block morphology are related to response to cardiac resynchronization therapy (CRT). A novel time-frequency analysis of the QRS complex may provide additional information in predicting response to CRT.

METHODS

Signal-averaged electrocardiograms were prospectively recorded, before CRT, in orthogonal leads and QRS decomposition in three frequency bands was performed using the Morlet wavelet transformation.

RESULTS

Thirty eight patients (age 65±10years, 31 males) were studied. CRT responders (n=28) had wider baseline QRS compared to non-responders and lower QRS energies in all frequency bands. The combination of QRS duration and mean energy in the high frequency band had the best predicting ability (AUC 0.833, 95%CI 0.705-0.962, p=0.002) followed by the maximum energy in the high frequency band (AUC 0.811, 95%CI 0.663-0.960, p=0.004).

CONCLUSIONS

Wavelet transformation of the QRS complex is useful in predicting response to CRT.

R peak detection in electrocardiogram signal based on an optimal combination of wavelet transform, hilbert transform, and adaptive thresholding

Electrocardiogram (ECG) is one of the most common biological signals which play a significant role in the diagnosis of heart diseases. One of the most important parts of ECG signal processing is interpretation of QRS complex and obtaining its characteristics. R wave is one of the most important sections of this complex, which has an essential role in diagnosis of heart rhythm irregularities and also in determining heart rate variability (HRV). This paper employs Hilbert and wavelet transforms as well as adaptive thresholding method to investigate an optimal combination of these signal processing techniques for the detection of R peak. In the experimental sections of this paper, the proposed algorithms are evaluated using both ECG signals from MIT-BIH database and synthetic data simulated in MATLAB environment with different arrhythmias, artifacts, and noise levels. Finally, by using wavelet and Hilbert transforms as well as by employing adaptive thresholding technique, an optimal combinational method for R peak detection namely WHAT is obtained that outperforms other techniques quantitatively and qualitatively.