ECG Method Research Articles

How to perform an electrocardiogram in an awake pond slider turtle (Trachemys scripta): a comparative study of five noninvasive methodologies.

To compare multiple noninvasive ECG methods in pond sliders based upon repeatability, ability to recognize standard waveforms, and measurability. The study was performed from November 2023 through January 2024. Ten healthy adult pond turtles were enrolled in the study. ECG tracings were obtained using 4 previously reported and 1 novel ECG methodology, using adhesive patches applied to the prehumeral fossae and abdominal scutes. The 50 ECG tracings were blinded by method and turtle, randomized for evaluation by 4 observers, and assessed for quality on a scale from 0 to 3. Interobserver and intraobserver intraclass correlation coefficients for all tracings were 0.84 and 0.97, respectively, indicating an almost perfect agreement. The average score amongst the observers for each tracing was then averaged by method, ranging from 0.875 to 2.15. The novel method demonstrated a collective average of 2.15 and was the highest scoring method for 8 of 10 turtles. Electrocardiogram utilizing methods that apply adhesive patches to the prehumeral fossae and either the abdominal scutes of the plastron or prefemoral fossae in pond turtles can be performed to produce recognizable waveforms. Diagnostic tools, such as ECGs, are imperative to enhance veterinary care in nonconventional species, particularly with the rising trend of exotic pets worldwide.

Genesis of ischemic ST segment changes: A study using precordial bipolar leads and regional vectorcardiograms

BackgroundPrecordial Bipolar Leads (PBLs), Weighted Unipolar Leads (WUL), and Regional Vectorcardiograms (RVCGs) are constructed using the same data recorded by a standard 12‑lead ECG, but they provide additional information not visible in the standard 12‑lead ECG (ECG) tracings. ObjectivesIn previous studies during balloon occlusion of the LAD and RCA, we observed a complete ischemic inversion of the QRS waves, with folding of the loop and ST segment shift. In the present study, we aim to investigate this abnormality using new ECG methods. We hypothesize that utilizing PBL, WUL, and RVCG in patients with ischemia caused by total acute coronary artery occlusion enables the detection of specific abnormalities—such as changes in waveform time/amplitude, the presence of the omega sign, distortion and folding of RVCG loops, and alterations in loop direction in both the transverse and frontal planes—that are not easily discernible with a standard 12‑lead ECG. This enhanced detection aids in understanding the mechanisms underlying electrocardiographic changes and may assist in managing patients when diagnostic uncertainties arise. MethodsThirty-three patients undergoing elective PTCA were studied before and after acute LAD (16 patients) or RCA (17 patients) occlusion, and their data were processed with new methods based on PBLs, WULs, and RVCGs. Results1. In acute ischemia due to occlusion of the LAD and RCA, the most important current of injury occurs in the right to left axis. This axis is underestimated by the standard 12‑lead ECG and only partially complemented by leads V3R and V4R. 2. The two-dimensional presentation detects a new sign (the omega sign), not detectable in the classic ECG, but almost always present in ischemia. It also allows for an accurate identification of the J point. 3. Ischemic R wave peak delay results in distortion and folding of the RVCG loop and causes displacement of the J point and the ST segment. 4. Wave inversion changes the loop direction in the transverse and frontal plane. ConclusionsPrecordial bipolar leads, weighted unipolar leads, and regional vectorcardiograms provide essential information omitted by the standard 12‑lead ECG.

Precordial activation sequences from low frequency analysis in left bundle branch block patients: left bundle branch area pacing vs right ventricular pacing

Abstract Introduction Left bundle branch area pacing (LBBAP) provides a more synchronous and physiological ventricular activation than conventional right ventricular pacing (RVP) in LBBB patients. QRS duration (QRSd) is the standard measurement for assessing depolarization synchrony, but it only provides information about the activation time and not about the activation sequence. Purpose Our aim is to assess the activation sequence by precordial activation delay (pAD) using a low-frequency (LF) ECG method comparing baseline and paced ECG in LBBAP and RVP patients. Methods Twelve-lead ECGs recordings were acquired from 29 patients with LBBB (16 LBBAP and 13 RVP) after 24 hours of sequential LBBAP or RVP. LF-ECG was employed for QRS-complex analysis. The activation time for each lead was computed and an activation sequence constructed by linking them. pAD was calculated as the time between the first and the last lead activation. pAD provides information about both, the delay in ventricular depolarization as indicated by its magnitude, and the depolarization direction (as it can take a positive or negative value indicating a left or right ventricle delay, respectively). Results At baseline, both groups (LBBAP and RVP) showed the latest activation at V5-V6, supported by positive median pAD values with no statistically significant differences between both groups (50 (21, 65) vs. 54 (17, 67) ms, p=0.93). LBBAP reduced V6 delay and pAD values compared to the baseline QRS (basal: 50 (21, 65) vs. paced: 2 (-18, 25) ms, p<0.001) while RVP did not exhibit any difference (basal: 54 (17, 67) vs. paced: 36 (19, 53) ms, p=0.33). LBBAP provided lower pAD values when compared to RVP (2 (-18, 25) vs. 36 (19, 53) ms, p<0.01). Conclusions pAD measured using a LF-ECG analysis is a feasible method to evaluate depolarization synchrony and provides complementary information to QRSd. In contrast to RVP, LBBAP generates a physiological ventricular activation sequence in patients with LBBB.Baseline patients characteristicsVentricular activation sequences and pAD

Short-term energy consumption prediction for university dormitory buildings based on energy consumption grouping by considering meteorological factors and teaching schedules

Accurate short-term energy consumption prediction is essential for studying renewable energy utilization in building technologies. University dormitory energy consumption is affected by meteorological factors and teaching schedules, presenting a more complex time series compared to residential buildings, rendering traditional methods unsuitable. Therefore, in the present study, we developed a model called energy consumption grouping-Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise-Bi-directional Long Short-Term Memory (ECG-ICEEMDAN-BILSTM) for predicting short-term energy consumption in university dormitory buildings. Model was tested using electricity consumption data from university dormitory buildings in cold regions of China. Based on the energy consumption characteristics, we identified two consumption patterns comprising high power energy consumption (HPEC) and low power energy consumption (LPEC). Using the ECG method, data with similar daily energy consumption distributions for HPEC and LPEC were grouped. Subsequently, individual prediction models were constructed based on ICEEMDAN-BILSTM for each specific energy consumption group. The experimental results showed the ECG-ICEEMDAN-BILSTM model obtained more accurate predictions compared with other neural network models. In addition, the model was more effective at forecasting the complex distribution of the HPEC pattern, with reductions of at least 16.21% and 15.82% in MAPE and PRMSE, respectively. Thus, study still can obtain valuable insights to address the problem of short-term prediction using complex time series.

Direct Lead Assignment: A Simple and Scalable Contrastive Learning Method for ECG and Its IoMT Applications

Direct Lead Assignment: A Simple and Scalable Contrastive Learning Method for ECG and Its IoMT Applications

Reliability of intra-atrial ECG method of insertion of central venous line through right internal jugular vein when compared to formula and radiological landmark method: a prospective randomized study

BackgroundIdeal position of central venous catheter tip should be within 2 cm above and 1 cm below superior vena cava–right atrium (SVC-RA) junction. The objective of the study was to compare intra-atrial ECG method of Central venous catheterization of right internal jugular vein (IJV) with traditional methods. A prospective randomized trial enrolling 90 patients were alternatively allocated to three groups and comparison of intra-atrial electrocardiography, radiological landmark and Pere’s formula method for correct positioning of central venous catheter tip were done and tip position were confirmed with post-procedural TEE (transesophageal echocardiography).ResultsCatheter tip was present at the ideal position in 100% cases in intra-atrial ECG method compared to only 23.4% in formula method and 93.3% in landmark method (p value 0.001). In intra-atrial method group, the central venous catheter tip was placed perfectly in all patients, position of the catheter tip was not acceptable in 71.4% of the patients where formula method is used and not acceptable in 11.1% when landmark method is used (p value 0.001). However, we did not encounter any catheter related complications in any of these groups.ConclusionsIntra-atrial ECG method carries the advantage of ideal positioning of the central venous catheter tip by right IJV route in almost all cases when compared to conventional formula and landmark method to some extent. Also, immediate confirmation and real time verification of central venous catheter (CVC) tip is possible, thereby avoids the need for post-procedural chest X-ray and other methods of central venous placement confirmation like arterial blood gas analysis etc., Hence, intra-atrial ECG method is cost effective and safer for confirmation of CVC tip in all the situations.

Commentary: A novel and effective ECG method to differentiate right from left ventricular outflow tract arrhythmias: angle-corrected V2S.

Commentary: A novel and effective ECG method to differentiate right from left ventricular outflow tract arrhythmias: angle-corrected V2S.

Localization of the ventricular pacing site from BSPM and standard 12-lead ECG: a comparison study

Inverse ECG imaging methods typically require 32–250 leads to create body surface potential maps (BSPM), limiting their routine clinical use. This study evaluated the accuracy of PaceView inverse ECG method to localize the left or right ventricular (LV and RV, respectively) pacing leads using either a 99-lead BSPM or the 12-lead ECG. A 99-lead BSPM was recorded in patients with cardiac resynchronization therapy (CRT) during sinus rhythm and sequential LV/RV pacing. The non-contrast CT was performed to localize precisely both ECG electrodes and CRT leads. From a BSPM, nine signals were selected to obtain the 12-lead ECG. Both BSPM and 12-lead ECG were used to localize the RV and LV lead, and the localization error was calculated. Consecutive patients with dilated cardiomyopathy, previously implanted with a CRT device, were enrolled (n = 19). The localization error for the RV/LV lead was 9.0 [IQR 4.8–13.6] / 7.7 [IQR 0.0–10.3] mm using the 12-lead ECG and 9.1 [IQR 5.4–15.7] / 9.8 [IQR 8.6–13.1] mm for the BSPM. Thus, the noninvasive lead localization using the 12-lead ECG was accurate enough and comparable to 99-lead BSPM, potentially increasing the capability of 12-lead ECG for the optimization of the LV/RV pacing sites during CRT implant or for the most favorable programming.

Siting Central Venous Catheters Precisely By Means of The ECG Method - A Reliability Study

Siting Central Venous Catheters Precisely By Means of The ECG Method - A Reliability Study

ECG Biometric Recognition: Review, System Proposal, and Benchmark Evaluation

ECGs have shown unique patterns to distinguish between different subjects and present important advantages compared to other biometric traits. However, the lack of public data and standard experimental protocols makes the evaluation and comparison of novel ECG methods difficult. In this study, we perform extensive analysis and comparison of different scenarios in ECG biometric recognition. We consider verification and identification tasks, single- and multi-session settings, and single- and multi-lead ECGs recorded with traditional and user-friendly devices. We also present ECGXtractor, a robust Deep Learning technology trained with an in-house large-scale database, and evaluate it with detailed experimental protocol and public databases. With the popular PTB database, we achieve Equal Error Rates of 0.14% and 2.06% in single- and multi-session verification. The results achieved prove the soundness of ECGXtractor across multiple scenarios and databases. We release the source code, experimental protocol details, and pre-trained models in GitHub to advance in the field.

Emerging ECG methods for acute coronary syndrome detection: Recommendations & future opportunities

Despite being the mainstay for the initial noninvasive assessment of patients with symptomatic coronary artery disease, the 12‑lead ECG remains a suboptimal diagnostic tool for myocardial ischemia detection with only acceptable sensitivity and specificity scores. Although myocardial ischemia affects the configuration of the QRS complex and the STT waveform, current guidelines primarily focus on ST segment amplitude, which constitutes a missed opportunity and may explain the suboptimal diagnostic performance of the ECG. This possible opportunity and the low cost and ease of use of the ECG provide compelling motivation to enhance the diagnostic accuracy of the ECG to ischemia detection. This paper describes numerous computational ECG methods and approaches that have been shown to dramatically increase ECG sensitivity to ischemia detection. Briefly, these emerging approaches can be conceptually grouped into one of the following four approaches: (1) leveraging novel ECG waveform features and signatures indicative of ischemic injury other than the classical ST-T amplitude measures; (2) applying body surface potentials mapping (BSPM)-based approaches to enhance the spatial coverage of the surface ECG to detecting ischemia; (3) developing an inverse ECG solution to reconstruct anatomical models of activation and recovery pathways to detect and localize injury currents; and (4) exploring artificial intelligence (AI)-based techniques to harvest ECG waveform signatures of ischemia. We present recent advances, shortcomings, and future opportunities for each of these emerging ECG methods. Future research should focus on the prospective clinical testing of these approaches to establish clinical utility and to expedite potential translation into clinical practice.

A Comparison of Alternative Approaches to MR Cardiac Triggering: A Pilot Study at 3 Tesla.

This pilot comparative study evaluates the usability of the alternative approaches to magnetic resonance (MR) cardiac triggering based on ballistocardiography (BCG): fiber-optic sensor (O-BCG) and pneumatic sensor (P-BCG). The comparison includes both the objective and subjective assessment of the proposed sensors in comparison with a gold standard of ECG-based triggering. The objective evaluation included several image quality assessment (IQA) parameters, whereas the subjective analysis was performed by 10 experts rating the diagnostic quality (scale 1 - 3, 1 corresponding to the best image quality and 3 the worst one). Moreover, for each examination, we provided the examination time and comfort rating (scale 1 - 3). The study was performed on 10 healthy subjects. All data were acquired on a 3 T SIEMENS MAGNETOM Prisma. In image quality analysis, all approaches reached comparable results, with ECG slightly outperforming the BCG-based methods, especially according to the objective metrics. The subjective evaluation proved the best quality of ECG (average score of 1.68) and higher performance of P-BCG (1.97) than O-BCG (2.03). In terms of the comfort rating and total examination time, the ECG method achieved the worst results, i.e. the highest score and the longest examination time: 2.6 and 10:49 s, respectively. The BCG-based alternatives achieved comparable results (P-BCG 1.5 and 8:06 s; OBCG 1.9, 9:08 s). This study confirmed that the proposed BCG-based alternative approaches to MR cardiac triggering offer comparable quality of resulting images with the benefits of reduced examination time and increased patient comfort.

Multiple electrocardiogram generator with single-lead electrocardiogram

Background and ObjectiveElectrocardiogram (ECG) is measured in various ways. The three main ECG measurement methods include resting ECG, Holter monitoring, and treadmill method. In standard ECG measurement methods, multiple electrodes are attached to the limb and chest. Limb and chest leads measure the frontal and sagittal planes of the heart, respectively. In this case, ECG signals are measured briefly up to 10 seconds. To measure ECG signals based on a single lead, wearable devices have been developed that could measure long-term ECG signals daily. ECG signals are vectors in the heart, which is a three-dimensional structure. Therefore, a single-lead measurement lacks detailed information. The objective of this study was to synthesize multiple ECGs from a single-lead ECG using a generative adversarial network (GAN). MethodsWe trained our model with two independent datasets and one combined dataset. For experiment 1, the PTB-XL dataset was used as the training set, and the China dataset was used as the test set. For experiment 2, the China dataset was used as the training set, and the PTB-XL was used as the test set. Optimized GAN models were obtained for each experiment and evaluated. ResultsThe Fréchet distance (FD) score and mean squared error (MSE) were used for evaluation. The FD and MSE scores for experiments 1 and 2 were 7.237 and 0.024, and 8.055 and 0.011, respectively. ConclusionWe proposed a method to overcome the limitations of modern ECG measurement methods. Low FD and MSE scores not only indicate the possibility but also the similarity between synthesized ECG and reference ECG when compared in ECG paper format. This indicates that the proposed method can be applied to wearable devices that measure single-lead ECG.

A randomised trial of intracavitary electrocardiography versus surface landmark measurement for central venous access device placement

Background: Malpositioned central venous access devices (CVADs) can lead to significant patient injury including central vein thrombosis and dysrhythmias. Intra-cavitary electrocardiography (IC ECG) has been recommended by peak professional bodies as an accurate alternative for bedside CVAD insertion, to reduce risk of malposition and allowing immediate use of the device. Our objective was to compare the effect of IC ECG on CVAD malposition compared to traditional institutional practice for CVAD placement. Methods: Randomised controlled trial of IC ECG CVAD insertion verses traditional CVAD insertion (surface landmark measurement with post insertion x ray). Patient recruitment was from December 2016 to July 2018. The setting was a 900-bed tertiary referral hospital based in South Western Sydney, Australia. Three hundred and forty-four adult patients requiring CVAD insertion for intravenous therapy, were enrolled and randomly allocated (1:1 ratio) to either IC-ECG ( n = 172) or traditional ( n = 172) CVAD insertion. Our primary outcome of interest was the rate of catheters not requiring repositioning after insertion (ready for use). Secondary outcomes were comparison of procedure time and cost. Results: Of the 172 patients allocated to the IC ECG method, 170 (99%) were ready for use immediately compared to 139 of the 172 (81%) in the traditional insertion group (difference, 95% confidence interval (CI): 18%, 11.9–24.1%). The total procedure time was mean 15 min (SD 8 min) for IC ECG and mean 36 min (SD 17 min) for traditional CVAD insertion (difference–19.9 min (95% CI–14.6 to −34.4). IC ECG guided CVAD insertion had a cost reduction of AUD $62.00 per procedure. Conclusions: Using IC-ECG resulted in nearly no requirement for post-insertion repositioning of CVADs resulting in savings in time and cost and virtually eliminating the need for radiographic confirmation. Trial registration: This trial is registered at the Australian New Zealand Clinical Trials Registry ( http://www.anzctr.org.au ). The registration number is ACTRN12620000919910.

Machine Learning for Electrocardiographic Features to Identify Left Atrial Enlargement in Young Adults: CHIEF Heart Study.

BackgroundLeft atrial enlargement (LAE) is associated with cardiovascular events. Machine learning for ECG parameters to predict LAE has been performed in middle- and old-aged individuals but has not been performed in young adults.MethodsIn a sample of 2,206 male adults aged 17–43 years, three machine learning classifiers, multilayer perceptron (MLP), logistic regression (LR), and support vector machine (SVM) for 26 ECG features with or without 6 biological features (age, body height, body weight, waist circumference, and systolic and diastolic blood pressure) were compared with the P wave duration of lead II, the traditional ECG criterion for LAE. The definition of LAE is based on an echocardiographic left atrial dimension > 4 cm in the parasternal long axis window.ResultsThe greatest area under the receiver operating characteristic curve is present in machine learning of the SVM for ECG only (77.87%) and of the MLP for all biological and ECG features (81.01%), both of which are superior to the P wave duration (62.19%). If the sensitivity is fixed to 70–75%, the specificity of the SVM for ECG only is up to 72.4%, and that of the MLP for all biological and ECG features is increased to 81.1%, both of which are higher than 48.8% by the P wave duration.ConclusionsThis study suggests that machine learning is a reliable method for ECG and biological features to predict LAE in young adults. The proposed MLP, LR, and SVM methods provide early detection of LAE in young adults and are helpful to take preventive action on cardiovascular diseases.

The intracavitary ECG method for tip location of ultrasound-guided centrally inserted central catheter in neonates

The correct position of the tip of a central venous access device is important in all patients, and especially in neonates. The traditional method of tip location (approximated intra-procedural length estimation + post procedural chest X-ray) is currently considered inaccurate and not cost-effective by most recent guidelines, which recommend the adoption of tip location by intracavitary electrocardiography (IC-ECG) whenever possible. This study prospectively investigated the applicability, the feasibility, the accuracy, and the safety IC-ECG for tip location in neonates requiring insertion of ultrasound-guided centrally inserted central venous catheters (CICCs) with caliber 3Fr or more. All catheter tip locations were verified using simultaneously both IC-ECG and ultrasound-based tip location, using the Neo-ECHOTIP protocol. A total of 105 neonates were enrolled. The applicability of IC-ECG was 100% since a P wave was evident on the surface ECG of all neonates recruited for the study. The feasibility was also 100% since an increase of the P-wave was detected in all cases. The accuracy was also 100%, since a perfect match between IC-ECG based tip location and ultrasound-based tip location was found. There were no adverse events directly or indirectly related to the IC-ECG technique; no arrhythmias occurred. When applied to ultrasound guided CICCs, tip location by IC-ECG is applicable and feasible in neonates, and it is safe and accurate.

25-річний досвід створення та впровадження інтелектуальних інформаційних технологій оброблення біометричних сигналів складної форми

Introduction. An important area of modern information technology application is medical diagnostics, which is based on computer processing of biomedical signals The purpose of the article is to provide information on the results of basic and applied research that has ensured the practical implementation of the ECG method (fasegraphy method) in various fields of application and to outline further prospects for these studies. Methods. The technology is based on a stochastic model of generating an artificial signal of complex shape in terms of internal and external distortions. Results. It is shown that the efficiency in extracting diagnostic information from biomedical signals in conditions of the real distortions, which are not always additive in nature, can be increased by switching from a scalar signal in the time domain to a cognitive image in the phase plane. Original algorithms of adaptive filtering and smoothing have been developed, which made it possible to obtain a numerical estimate of the first derivative of the distorted signal. Recovery of the useful signal (reference cycle) for distorted implementations is carried out by averaging the phase trajectories with the subsequent return to the time domain. To increase the reliability of additional diagnostic features of the ECG in the phase space is proposed and clinical data have proven their usefulness in terms of reducing the risk of misdiagnosis. The practical results of the implementation of the diagnostic complex FASEGRAF® have confirmed the effectiveness of fasegraphy in various fields of application. Plans for further prospective research are presented. Conclusions. Continuation of research allow to create new competitive information technologies and digital medicine devices.

Evaluation of ECG Recording Applications of Non-Physician Healthcare Workers Working in Emergency Departments

Aim: The aim of the study was to identify the right and wrong applications of non-physician healthcare workers working in the emergency department (ED) on the standard ECG method.
 
 Material and Methods: The study was conducted in the ED of two hospitals in Yozgat province. The data were collected in three stages, in which healthcare workers recording ECGs were observed, emergency medicine specialists evaluated each ECG recording, and the questionnaire on the ECG shooting method was applied. Frequency and percentage values in the descriptive statistics of the study and Pearson Correlation analysis were used to determine the relationship between variables.
 
 Results: There was no statistically significant relationship between healthcare workers' level of knowledge about recording ECG and the correct execution of the procedure (p>0.05). Emergency medicine specialists who interpreted the ECG reported that there was a situation that limited interpretation in nearly half of the ECG reports, which was due to the shooting error in 46% of them, and 22% of the ECG shootings were repeated. Chest electrodes were highly positioned incorrectly (100%-80%) in both theory and in practice.
 
 Conclusion: It was observed that there was no relationship between the knowledge of the healthcare professionals who recorded the ECG about the procedure and their behavior during the procedure, and there was at least one shooting error in almost half of the ECGs taken in the ED.

Pacing Electrocardiogram Detection With Memory-Based Autoencoder and Metric Learning.

Remote ECG diagnosis has been widely used in the clinical ECG workflow. Especially for patients with pacemaker, in the limited information of patient's medical history, doctors need to determine whether the patient is wearing a pacemaker and also diagnose other abnormalities. An automatic detection pacing ECG method can help cardiologists reduce the workload and the rates of misdiagnosis. In this paper, we propose a novel autoencoder framework that can detect the pacing ECG from the remote ECG. First, we design a memory module in the traditional autoencoder. The memory module is to record and query the typical features of the training pacing ECG type. The framework does not directly feed features of the encoder into the decoder but uses the features to retrieve the most relevant items in the memory module. In the training process, the memory items are updated to represent the latent features of the input pacing ECG. In the detection process, the reconstruction data of the decoder is obtained by the fusion features in the memory module. Therefore, the reconstructed data of the decoder tends to be close to the pacing ECG. Meanwhile, we introduce an objective function based on the idea of metric learning. In the context of pacing ECG detection, comparing the error of objective function of the input data and reconstructed data can be used as an indicator of detection. According to the objective function, if the input data does not belong to pacing ECG, the objective function may get a large error. Furthermore, we introduce a new database named the pacing ECG database including 800 patients with a total of 8,000 heartbeats. Experimental results demonstrate that our method achieves an average F1-score of 0.918. To further validate the generalization of the proposed method, we also experiment on a widely used MIT-BIH arrhythmia database.

The development of a new, simple electrocardiographic method for the estimation of the latest activated left ventricular site

Abstract Background Current cardiac resynchronization therapy (CRT) works by pacing the latest activated left ventricular (LV) site. The estimation of the location of the latest activated LV site (LALVS) may be important to determine the optimal position of the LV electrode during CRT or to predict the patient response to the current CRT technique devised to pace the LALVS usually present in patients with left bundle branch block (LBBB) pattern. Methods We used a modified 12-lead ECG algorithm originally devised and used by other authors* for a different purpose, to identify the segment of origin of ventricular tachycardia in the 16-segment American Heart Association LV model by analyzing the QRS axis in the limb and chest leads. We hypothesized that modifying this ECG algorithm by using the secondary ST vector axis instead of the QRS axis in the limb and chest leads, we can apply this ECG method to estimate the LALVS instead of the site of origin of the ventricular tachycardia. The resultant secondary ST vector is directed 180o away from the LALVS. Using this ECG method we determined the LALVS in 22 patients with LBBB and 20 patients with nonspecific intraventricular conduction disturbance (NICD) patterns and heart failure. To validate the ECG method, we also estimated the LALVS by echocardiography using 3D parametric imaging and 2D speckle tracking. Results The LALVS determined by the electrocardiographic method and echocardiogrpahy in the 16-segment model matched (was in the same or adjacent segment) in 38/42 (90.5%) patients and among these patients complete matching (the LALVSs were in the same segment) was found in 16/38 (42%) and partial matching (the LALVSs were in adjacent segments) in 22/38 (58%) patients. When the LBBB and NICD groups were separated to patients with ≥150 ms and <150 ms QRS duration subgroups, the LALVSs of the ≥150 ms subgroup were almost exclusively in the anterolateral (or anterior) or inferolateral areas and those of the <150 ms subgroup were in the above mentioned areas or sometimes at other sites located remote from these areas. Conclusions The novel, simple surface electrocardiographic method could as reliably estimate the approximate location of LALVS as echocardiography. The possible explanation for the effectivity of CRT in patients with sinus rhythm with intraventricular conduction disturbance and ≥150 ms QRS duration is that their LALVS is at the same most distant areas (anterolateral, anterior, inferolateral) from the initial septal activation site where the LV electrodes are positioned during application of the current CRT technique. Funding Acknowledgement Type of funding sources: None.