The effect of precordial lead displacement on ECG morphology

Empagliflozin's role in reducing ventricular repolarization heterogeneity: insights into cardiovascular mortality decline from the EMPATHY-HEART trial

BACKGROUND

The incidence of myocardial infarction (MI) and sudden cardiac death (SCD) is significantly higher in individuals with Type 2 Diabetes Mellitus (T2DM) than in the general population. Strategies for the prevention of fatal arrhythmias are often insufficient, highlighting the need for additional non-invasive diagnostic tools. The T-wave heterogeneity (TWH) index measures variations in ventricular repolarization and has emerged as a promising predictor for severe ventricular arrhythmias. Although the EMPA-REG trial reported reduced cardiovascular mortality with empagliflozin, the underlying mechanisms remain unclear. This study investigates the potential of empagliflozin in mitigating cardiac electrical instability in patients with T2DM and coronary heart disease (CHD) by examining changes in TWH.

METHODS

Participants were adult outpatients with T2DM and CHD who exhibited TWH > 80 µV at baseline. They received a 25 mg daily dose of empagliflozin and were evaluated clinically including electrocardiogram (ECG) measurements at baseline and after 4 weeks. TWH was computed from leads V4, V5, and V6 using a validated technique. The primary study outcome was a significant (p < 0.05) change in TWH following empagliflozin administration.

RESULTS

An initial review of 6,000 medical records pinpointed 800 patients for TWH evaluation. Of these, 412 exhibited TWH above 80 µV, with 97 completing clinical assessments and 90 meeting the criteria for high cardiovascular risk enrollment. Empagliflozin adherence exceeded 80%, resulting in notable reductions in blood pressure without affecting heart rate. Side effects were generally mild, with 13.3% experiencing Level 1 hypoglycemia, alongside infrequent urinary and genital infections. The treatment consistently reduced mean TWH from 116 to 103 µV (p = 0.01).

CONCLUSIONS

The EMPATHY-HEART trial preliminarily suggests that empagliflozin decreases heterogeneity in ventricular repolarization among patients with T2DM and CHD. This reduction in TWH may provide insight into the mechanism behind the decreased cardiovascular mortality observed in previous trials, potentially offering a therapeutic pathway to mitigate the risk of severe arrhythmias in this population.

TRIAL REGISTRATION

NCT: 04117763.

Limited Relationship Between Echocardiographic Measures and Electrocardiographic Markers of Left Ventricular Size in Healthy Children

Pediatric ECG standards have been defined without echocardiographic confirmation of normal anatomy. The Pediatric Heart Network Normal Echocardiogram Z-score Project provides a racially diverse group of healthy children with normal echocardiograms. We hypothesized that ECG and echocardiographic measures of left ventricular (LV) dimensions are sufficiently correlated in healthy children to imply a clinically meaningful relationship. This was a secondary analysis of a previously described cohort including 2170 digital ECGs. The relationship between 6 ECG measures associated with LV size were analyzed with LV Mass (LVMass-z) and left ventricular end-diastolic volume (LVEDV-z) along with 11 additional parameters. Pearson or Spearman correlations were calculated for the 78 ECG-echocardiographic pairs with regression analyses assessing the variance in ECG measures explained by variation in LV dimensions and demographic variables. ECG/echocardiographic measurement correlations were significant and concordant in 41/78 (53%), though many were significant and discordant (13/78). Of the 6 ECG parameters, 5 correlated in the clinically predicted direction for LV Mass-z and LVEDV-z. Even when statistically significant, correlations were weak (0.05-0.24). R2 was higher for demographic variables than for echocardiographic measures or body surface area in all pairs, but remained weak (R2 ≤ 0.17). In a large cohort of healthy children, there was a positive association between echocardiographic measures of LV size and ECG measures of LVH. These correlations were weak and dependent on factors other than echocardiographic or patient derived variables. Thus, our data support deemphasizing the use of solitary, traditional measurement-based ECG markers traditionally thought to be characteristic of LVH as standalone indications for further cardiac evaluation of LVH in children and adolescents.

Personalized screening before subcutaneous cardioverter-defibrillator implantation: Usefulness and outcomes in clinical practice-the S-ICD screening SIS prospective study

BACKGROUND

Electrocardiographic screening before subcutaneous implantable cardioverter-defibrillator (S-ICD) implantation is unsuccessful in around 10% of cases. A personalized screening method, by slightly moving the electrodes, to obtain a better R/T ratio has been described to overcome traditional screening failure.

OBJECTIVE

The objectives of the SIS study were to assess to what extent a personalized screening method improves eligibility for S-ICD implantation and to evaluate the inappropriate shock rate after such screening success.

METHODS

All consecutive patients eligible for an S-ICD implantation were prospectively recruited across 20 French centers between December 2019 and January 2022. In case of traditional screening failure, patients received a second personalized screening. If at least 1 vector was positive, the personalized screening was considered successful, and the patient was eligible for implantation.

RESULTS

The study included 474 patients (mean age, 50.4 ± 14.1 years; 77.4% men). Traditional screening was successful in 456 (96.2%) cases. This figure rose to 98.3% (n = 466; P = .002) when personalized screening was performed. All patients implanted after successful personalized screening had correct signal detection on initial device interrogation. Nevertheless, after 1-year follow-up, 3 of the 7 patients (43%) implanted with personalized screening experienced inappropriate shock vs 18 of the 427 patients (4.2%) with traditional screening and S-ICD implantation (P = .003).

CONCLUSION

Traditional S-ICD screening was successful in our study in a high proportion of patients. Considering the small improvement in success of screening and a higher rate of inappropriate shock, a strategy of personalized screening cannot be routinely recommended.

CLINICALTRIALS

gov identifier: NCT04101253.

Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion

An electrocardiogram (ECG) is used to observe the electrical activity of the heart via electrodes on the body surface. Recently, an ECG with fewer electrodes, such as a bipolar ECG in which two electrodes are attached to the chest, has been employed as wearable devices. However, the effect of different geometrical factors and electrode-pair locations on the amplitude and waveform of ECG signals remains unclear. In this study, we computationally evaluated the effects of body morphology, heart size and orientation, and electrode misalignment on ECG signals for 48 scenarios using 35 bipolar electrode pairs (1680 waveforms) with a dynamic time warping (DTW) algorithm. It was observed that the physique of the human body model predominantly affected the amplitude and waveform of the ECG signals. A multivariate analysis indicated that the heart-electrode distance and the solid angle of the heart from the electrode characterized the amplitude and waveform of the ECG signals, respectively. Furthermore, the electrode locations for less individual variability and less waveform distortion were close to the location of electrodes V2 and V3 in the standard 12-lead. These findings will facilitate the placement of ECG electrodes and interpretation of the measured ECG signals for wearable devices.

Performing Accurate Standard 12 Lead ECGs on patients with Burns to the Chest

The use of the electrocardiogram (ECG) in critical care settings is a long-established cardiovascular monitoring tool. The effectiveness of the routine 12-lead ECG relies on accurate lead placement that is consistent and replicable. Improper lead placement may display erroneous ECG patterns and affect patient management decisions.1,2 In the setting of an acute injury, such as a torso burn to the ventral surface, accurate lead placement may be compromised or impossible. The regional burn center, which is part of our organization, sees approximately 500 patients per year. Of those patients, burns to the chest accounted for 21% of admissions during 2020 and 2021. This significant fraction of burn injury patients requires modification of our standard approach to provide an accurate ECG. Baseline ECGs are routinely acquired on the burn unit per protocol and for monitoring of patient response to numerous pharmaceutical therapies.

[Diagnostic predictive value of liver biopsy for clinical aspects]

Background

The quest for improved diagnosis and treatment in home health care models has led to the development of wearable medical devices for remote vital signs monitoring. An accurate signal and a high diagnostic yield are critical for the cost-effectiveness of wearable health care monitoring systems and their widespread application in resource-constrained environments. Despite technological advances, the information acquired by these devices can be contaminated by motion artifacts (MA) leading to misdiagnosis or repeated procedures with increases in associated costs. This makes it necessary to develop methods to improve the quality of the signal acquired by these devices.

Objective

We aimed to present a novel method for electrocardiogram (ECG) signal denoising to reduce MA. We aimed to analyze the method’s performance and to compare its performance to that of existing approaches.

Methods

We present the novel Redundant denoising Independent Component Analysis method for ECG signal denoising based on the redundant and simultaneous acquisition of ECG signals and movement information, multichannel processing, and performance assessment considering the information contained in the signal waveform. The method is based on data including ECG signals from the patient’s chest and back, the acquisition of triaxial movement signals from inertial measurement units, a reference signal synthesized from an autoregressive model, and the separation of interest and noise sources through multichannel independent component analysis.

Results

The proposed method significantly reduced MA, showing better performance and introducing a smaller distortion in the interest signal compared with other methods. Finally, the performance of the proposed method was compared to that of wavelet shrinkage and wavelet independent component analysis through the assessment of signal-to-noise ratio, dynamic time warping, and a proposed index based on the signal waveform evaluation with an ensemble average ECG.

Conclusions

Our novel ECG denoising method is a contribution to converting wearable devices into medical monitoring tools that can be used to support the remote diagnosis and monitoring of cardiovascular diseases. A more accurate signal substantially improves the diagnostic yield of wearable devices. A better yield improves the devices’ cost-effectiveness and contributes to their widespread application.

Motion Artifact Reduction in Electrocardiogram Signals Through a Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems: Algorithm Development and Validation

BACKGROUND

The quest for improved diagnosis and treatment in home health care models has led to the development of wearable medical devices for remote vital signs monitoring. An accurate signal and a high diagnostic yield are critical for the cost-effectiveness of wearable health care monitoring systems and their widespread application in resource-constrained environments. Despite technological advances, the information acquired by these devices can be contaminated by motion artifacts (MA) leading to misdiagnosis or repeated procedures with increases in associated costs. This makes it necessary to develop methods to improve the quality of the signal acquired by these devices.

OBJECTIVE

We aimed to present a novel method for electrocardiogram (ECG) signal denoising to reduce MA. We aimed to analyze the method's performance and to compare its performance to that of existing approaches.

METHODS

We present the novel Redundant denoising Independent Component Analysis method for ECG signal denoising based on the redundant and simultaneous acquisition of ECG signals and movement information, multichannel processing, and performance assessment considering the information contained in the signal waveform. The method is based on data including ECG signals from the patient's chest and back, the acquisition of triaxial movement signals from inertial measurement units, a reference signal synthesized from an autoregressive model, and the separation of interest and noise sources through multichannel independent component analysis.

RESULTS

The proposed method significantly reduced MA, showing better performance and introducing a smaller distortion in the interest signal compared with other methods. Finally, the performance of the proposed method was compared to that of wavelet shrinkage and wavelet independent component analysis through the assessment of signal-to-noise ratio, dynamic time warping, and a proposed index based on the signal waveform evaluation with an ensemble average ECG.

CONCLUSIONS

Our novel ECG denoising method is a contribution to converting wearable devices into medical monitoring tools that can be used to support the remote diagnosis and monitoring of cardiovascular diseases. A more accurate signal substantially improves the diagnostic yield of wearable devices. A better yield improves the devices' cost-effectiveness and contributes to their widespread application.

Using the Apple Watch to Record Multiple-Lead Electrocardiograms in Detecting Myocardial Infarction: Where Are We Now?

Although the outcome after myocardial infarction depends on the time to treatment, a delay between symptom onset and treatment is common. Apple Watch, a popular wearable device, provides the ability to perform an electrocardiogram. We review the progress made in using the Apple Watch to record multiple electrocardiogram leads for diagnosing myocardial infarction. Although the data are encouraging, many limitations remain, and more research is needed. Nevertheless, the Apple Watch could eventually serve as a self-check tool for patients who have chest pains or other symptoms of myocardial infarction, thus substantially decreasing the time to treatment and improving the outcome after myocardial infarction.

Learning to Disentangle Inter-Subject Anatomical Variations in Electrocardiographic Data

OBJECTIVE

This work investigates the possibility of disentangled representation learning of inter-subject anatomical variations within electrocardiographic (ECG) data.

METHODS

Since ground truth anatomical factors are generally not known in clinical ECG for assessing the disentangling ability of the models, the presented work first proposes the SimECG data set, a 12-lead ECG data set procedurally generated with a controlled set of anatomical generative factors. Second, to perform such disentanglement, the presented method evaluates and compares deep generative models with latent density modeled by nonparametric Indian Buffet Process to account for the complex generative process of ECG data.

RESULTS

In the simulated data, the experiments demonstrate, for the first time, concrete evidence of the possibility to disentangle key generative anatomical factors within ECG data in separation from task-relevant generative factors. We achieve a disentanglement score of 92.1% while disentangling five anatomical generative factors and the task-relevant generative factor. In both simulated and real-data experiments, this work further provides quantitative evidence for the benefit of disentanglement learning on the downstream clinical task of localizing the origin of ventricular activation. Overall, the presented method achieves an improvement of around 18.5%, and 11.3% for the simulated dataset, and around 7.2%, and 3.6% for the real dataset, over baseline CNN, and standard generative model, respectively.

CONCLUSION

These results demonstrate the importance as well as the feasibility of the disentangled representation learning of inter-subject anatomical variations within ECG data.

SIGNIFICANCE

This work suggests the important research direction to deal with the well-known challenge posed by the presence of significant inter-subject variations during an automated analysis of ECG data.

CineECG: A novel method to image the average activation sequence in the heart from the 12-lead ECG

The standard 12-lead electrocardiogram (ECG) is a diagnostic tool to asses cardiac electrical activity. The vectorcardiogram is a related tool that represents that activity as the direction of a vector. In this work we investigate CineECG, a new 12-lead ECG based analysis method designed to directly estimate the average cardiac anatomical location of activation over time. We describe CineECG calculation and a novel comparison parameter, the average isochrone position (AIP). In a model study, fourteen different activation sequences were simulated and corresponding 12-lead ECGs were computed. The CineECG was compared to AIP in terms of location and direction. In addition, 67-lead body surface potential maps from ten patients were used to study the sensitivity of CineECG to electrode mispositioning and anatomical model selection. Epicardial activation maps from four patients were used for further evaluation. The average distance between CineECG and AIP across the fourteen sequences was 23.7 ± 2.4 mm, with significantly better agreement in the terminal (27.3 ± 5.7 mm) versus the initial QRS segment (34.2 ± 6.1 mm). Up to four cm variation in electrode positioning produced an average distance of 6.5 ± 4.5 mm between CineECG trajectories, while substituting a generic heart/torso model for a patient-specific one produced an average difference of 6.1 ± 4.8 mm. Dominant epicardial activation map features were recovered. Qualitatively, CineECG captured significant features of activation sequences and was robust to electrode misplacement. CineECG provides a realistic representation of the average cardiac activation in normal and diseased hearts. In particular, the terminal segment of the CineECG might be useful to detect pathology.

ECG Signal Quality Assessments of a Small Bipolar Single-Lead Wearable Patch Sensor

PURPOSE

There is an increasing clinical interest in the adoption of small single-lead wearable ECG sensors for continuous cardiac monitoring. The purpose of this work is to assess ECG signal quality of such devices compared to gold standard 12-lead ECG.

METHODS

The ECG signal from a 1-lead patch was systematically compared to the 12-lead ECG device in thirty subjects to establish its diagnostic accuracy in terms of clinically relevant signal morphology, wave representation, fiducial markers and interval and wave duration. One minute ECG segments with good signal quality was selected for analysis and the features of ECG were manually annotated for comparative assessment.

RESULTS

The patch showed closest similarity based on correlation and normalized root-mean-square error to the standard ECG leads I, II, [Formula: see text] and [Formula: see text]. P-wave and QRS complexes in the patch showed sensitivity (Se) and positive predictive value (PPV) of at least 99.8% compared to lead II. T-wave representation showed Se and PPV of at least 99.9% compared to lead [Formula: see text] and [Formula: see text]. Mean errors for onset and offset of the ECG waves, wave durations, and ECG intervals were within 2 samples based on 125Hz patch ECG sampling frequency.

CONCLUSION

This study demonstrates the diagnostic capability with similar morphological representation and reasonable timing accuracy of ECG signal from a patch sensor compared to 12-lead ECG. The advantages and limitations of small bipolar single-lead wearable patch sensor compared to 12-lead ECG are discussed in the context of relevant differences in ECG signal for clinical applications.

Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology

Personalized models of cardiac electrophysiology (EP) that match clinical observation with high fidelity, referred to as cardiac digital twins (CDTs), show promise as a tool for tailoring cardiac precision therapies. Building CDTs of cardiac EP relies on the ability of models to replicate the ventricular activation sequence under a broad range of conditions. Of pivotal importance is the His-Purkinje system (HPS) within the ventricles. Workflows for the generation and incorporation of HPS models are needed for use in cardiac digital twinning pipelines that aim to minimize the misfit between model predictions and clinical data such as the 12 lead electrocardiogram (ECG). We thus develop an automated two stage approach for HPS personalization. A fascicular-based model is first introduced that modulates the endocardial Purkinje network. Only emergent features of sites of earliest activation within the ventricular myocardium and a fast-conducting sub-endocardial layer are accounted for. It is then replaced by a topologically realistic Purkinje-based representation of the HPS. Feasibility of the approach is demonstrated. Equivalence between both HPS model representations is investigated by comparing activation patterns and 12 lead ECGs under both sinus rhythm and right-ventricular apical pacing. Predominant ECG morphology is preserved by both HPS models under sinus conditions, but elucidates differences during pacing.

Regadenoson-induced T-wave heterogeneity complements coronary stenosis detection by myocardial perfusion imaging in men and women

AIMS

We analysed whether incorporating electrocardiographic interlead T-wave heterogeneity (TWH) with myocardial perfusion imaging (MPI) during pharmacologic stress improves detection of flow-limiting lesions (FLL).

METHODS AND RESULTS

Medical records of all 103 patients at our institution who underwent stress testing with regadenoson (0.4 mg IV bolus) within 3 months of coronary angiography from September 2017 to March 2019 were studied. Cases (N = 59) had angiographically significant FLL (≥50% of left main or ≥70% of other epicardial coronary arteries ≥2 mm in diameter); controls (N = 44) were normal or had non-FLL. TWH, i.e., interlead splay of T waves, was assessed from precordial leads V4-6 by second central moment analysis. Maximum TWHV4-6 levels during regadenoson stress were 68% higher in cases than in controls (P < 0.0001). TWHV4-6 generated areas under the receiver-operating characteristic (ROC) curve of 0.79 in men (P < 0.0001) and 0.71 in women (P = 0.007). In men, the ROC-guided 54-µV TWHV4-6 cut-point for FLL produced adjusted odds of 7.3 [95% confidence interval (CI): 1.3-41.5, P = 0.03], 79% sensitivity, and 78% specificity. In women, the ROC-guided 35-µV TWHV4-6 cut-point produced adjusted odds of 4.5 (95% CI: 1.1-18.9, P = 0.04), 84% sensitivity, and 52% specificity. Adding TWHV4-6 to MPI determinations reduced false-positive results by 70%, more than doubled true-negative results, and improved adjusted odds ratio to 6.8 (95% CI: 2.2-21.4, P = 0.001) with specificity of 78% in men and 86% in women.

CONCLUSION

This observational study is the first to demonstrate the benefit of combining TWHV4-6 with MPI to enhance FLL detection during MPI with regadenoson in both men and women.

Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes' Location and Motion Artifacts Reduction for Wearable Monitoring Applications

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by World Health Organization. Some wearables devices have been developed to monitor the Electrocardiographic in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an Electrocardiographic signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effects of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain Electrocardiographic signals, the result was compared with a computational model of the heart behavior through the Ensemble Average Electrocardiographic, Dynamic Time Warping and Signal-to-Noise Ratio methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the Electrocardiographic signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6 cm at most from the suggested location by the Einthoven triangle in Mason–Likar’s method.

Accuracy of ECG chest electrode placements by paramedics: an observational study

Background:

The use of the 12-lead electrocardiogram (ECG) is common in sophisticated pre-hospital emergency medical services but its value depends upon accurate placement of the ECG electrodes. Several studies have shown widespread variation in the placement of chest electrodes by other health professionals but no studies have addressed the accuracy of paramedics. The main objective of this study was to ascertain the accuracy of the chest lead placements by registered paramedics.

Methods:

Registered paramedics who attended the Emergency Services Show in Birmingham in September 2018 were invited to participate in this observational study. Participants were asked to place the chest electrodes on a male model in accordance with their current practice. Correct positioning was determined against the Society for Cardiological Science and Technology’s 2017 clinical guidelines for recording a standard 12-lead ECG, with a tolerance of 19 mm being deemed acceptable based upon previous studies.

Results:

Fifty-two eligible participants completed the study. Measurement of electrode placement in the vertical and horizontal planes showed a high level of inaccuracy, with 3/52 (5.8%) participants able to accurately place all chest electrodes. In leads V₁–V₃, the majority of incorrect placements were related to vertical displacement, with most participants able to identify the correct horizontal position. In V₄, the tendency was to place the electrode too low and to the left of the pre-determined position, while V₅ tended to be below the expected positioning but in the correct horizontal alignment. There was a less defined pattern of error in V₆, although vertical displacement was more likely than horizontal displacement.

Conclusions:

Our study identified a high level of variation in the placement of chest ECG electrodes, which could alter the morphology of the ECG. Correct placement of V₁ improved placement of other electrodes. Improved initial and refresher training should focus on identification of landmarks and correct placement of V₁.

Reliable Deep Learning-Based Detection of Misplaced Chest Electrodes During Electrocardiogram Recording: Algorithm Development and Validation

Background

A 12-lead electrocardiogram (ECG) is the most commonly used method to diagnose patients with cardiovascular diseases. However, there are a number of possible misinterpretations of the ECG that can be caused by several different factors, such as the misplacement of chest electrodes.

Objective

The aim of this study is to build advanced algorithms to detect precordial (chest) electrode misplacement.

Methods

In this study, we used traditional machine learning (ML) and deep learning (DL) to autodetect the misplacement of electrodes V1 and V2 using features from the resultant ECG. The algorithms were trained using data extracted from high-resolution body surface potential maps of patients who were diagnosed with myocardial infarction, diagnosed with left ventricular hypertrophy, or a normal ECG.

Results

DL achieved the highest accuracy in this study for detecting V1 and V2 electrode misplacement, with an accuracy of 93.0% (95% CI 91.46-94.53) for misplacement in the second intercostal space. The performance of DL in the second intercostal space was benchmarked with physicians (n=11 and age 47.3 years, SD 15.5) who were experienced in reading ECGs (mean number of ECGs read in the past year 436.54, SD 397.9). Physicians were poor at recognizing chest electrode misplacement on the ECG and achieved a mean accuracy of 60% (95% CI 56.09-63.90), which was significantly poorer than that of DL (P<.001).

Conclusions

DL provides the best performance for detecting chest electrode misplacement when compared with the ability of experienced physicians. DL and ML could be used to help flag ECGs that have been incorrectly recorded and flag that the data may be flawed, which could reduce the number of erroneous diagnoses.

Feasibility study of a 3D camera to reduce electrode repositioning errors during longitudinal ECG acquisition

INTRODUCTION

Longitudinal monitoring of sometimes subtle waveform changes of the 12‑lead electrocardiogram (ECG) is complicated by patient-specific and technical factors, such as the inaccuracy of electrode repositioning. This feasibility study uses a 3D camera to reduce electrode repositioning errors, reduce ECG waveform variability and enable detailed longitudinal ECG monitoring.

METHODS

Per subject, three clinical ECGs were obtained during routine clinical follow-up. Additionally, two ECGs were recorded guided by two 3D cameras, which were used to capture the precordial electrode locations and direct electrode repositioning. ECG waveforms and parameters were quantitatively compared between 3D camera guided ECGs and clinical ECGs. Euclidian distances between original and repositioned precordial electrodes from 3D guided ECGs were measured.

RESULTS

Twenty subjects (mean age 65.1 ± 8.2 years, 35% females) were included. The ECG waveform variation between routine ECGs was significantly higher compared to 3D guided ECGs, for both the QRS complex (correlation coefficient = 0.90 vs 0.98, p < 0.001) and the STT segment (correlation coefficient = 0.88 vs. 0.96, p < 0.001). QTc interval variation was reduced for 3D camera guided ECGs compared to routine clinical ECGs (5.6 ms vs. 9.6 ms, p = 0.030). The median distance between 3D guided repositioned electrodes was 10.0 [6.4-15.2] mm, and did differ between males and females (p = 0.076).

CONCLUSIONS

3D guided repositioning of precordial electrodes resulted in, a low repositioning error, higher agreement between waveforms of consecutive ECGs and a reduction of QTc variation. These findings suggest that longitudinal monitoring of disease progression using 12‑lead ECG waveforms is feasible in clinical practice.

T-wave heterogeneity in standard resting 12-lead ECGs is associated with 90-day cardiac mortality in women following emergency department admission: A nested case-control study

Background

We investigated whether T‐wave heterogeneity (TWH) can identify patients who are at risk for near‐term cardiac mortality.

Methods

A nested case–control analysis was performed in the 888 patients admitted to the Emergency Department (ED) of our medical center in July through September 2018 who had ≥2 serial troponin measurement tests within 6 hr for acute coronary syndrome evaluation to rule‐in or rule‐out the presence of acute myocardial infarction. Patients who died from cardiac causes during 90 days after ED admission were considered cases (n = 20; 10 women) and were matched 1:4 on sex and age with patients who survived during this period (n = 80, 40 women). TWH, that is, interlead splay of T waves, was automatically assessed from precordial leads by second central moment analysis.

Results

TWH_V4‐6 was significantly elevated at ED admission in 12‐lead resting ECGs of female patients who died of cardiac causes during the following 90 days compared to female survivors (100 ± 14.9 vs. 40 ± 3.6 µV, p < .0001). TWH_V4‐6 generated areas under the receiver‐operating characteristic (ROC) curve (AUC) of 0.933 in women (p < .0001) and 0.573 in men (p = .4). In women, the ROC‐guided 48‐µV TWH_V4‐6 cut point for near‐term cardiac mortality produced an adjusted odds ratio of 121.37 (95% CI: 2.89–6,699.84; p = .02) with 100% sensitivity and 82.5% specificity. In Kaplan–Meier survival analysis, TWH_V4‐6 ≥ 48 µV predicted cardiac mortality in women during 90‐day follow‐up with a hazard ratio of 27.84 (95% CI: 7.29–106.36, p < .0001).

Conclusion

Elevated TWH_V4‐6 is associated with near‐term cardiac mortality among women evaluated for acute coronary syndrome.

The Reconstruction of a 12-Lead Electrocardiogram from a Reduced Lead Set Using a Focus Time-Delay Neural Network

BACKGROUND

The 12-lead electrocardiogram (ECG) is the gold-standard ECG method used by cardiologists. However, accurate electrode placement is difficult and time consuming, and can lead to incorrect interpretation.

OBJECTIVES

The objective of this study was to accurately reconstruct a full 12-lead ECG from a reduced lead set.

METHODS

Five-electrode placement was used to generate leads I, II, III, aVL, aVR, aVF and V2. These seven leads served as inputs to the focus time-delay neural network (FTDNN) which derived the remaining five precordial leads (V1, V3-V6). An online archived medical database containing 549 cases of ECG recordings was used to train, validate and test the FTDNN.

RESULTS

After removing outliers, the reconstructed leads exhibited correlation values of between 0.8609 and 0.9678 as well as low root mean square error values of between 123 μV and 245 μV across all cases, for both healthy controls and cardiovascular disease subgroups except the bundle branch block disease subgroup. The results of the FTDNN method compared favourably to those of prior lead reconstruction methods.

CONCLUSIONS

A standard 12-lead ECG was successfully reconstructed with high quantitative correlations from a reduced lead set using only five electrodes, of which four were placed on the limbs. Less reliance on precordial leads will aid in the reduction of electrode placement errors, ultimately improving ECG lead accuracy and reduce the number of cases that are incorrectly diagnosed.

Exercise and pharmacologic stress-induced interlead T-wave heterogeneity analysis to detect clinically significant coronary artery stenosis

BACKGROUND

Despite widespread use of ETT and vasodilator-stress with myocardial perfusion imaging (MPI) for noninvasive detection of flow-limiting coronary artery disease, there is continued need to improve diagnostic accuracy. We examined whether measurement of interlead T-wave heterogeneity (TWH) during exercise tolerance testing (ETT) or pharmacologic stress testing improves detection of stenoses in large epicardial coronary arteries.

METHODS

All 137 patients at our institution who underwent diagnostic coronary angiography within 0 to 5 days after ETT (N = 81) or dipyridamole IV infusion (N = 58) in 2016 were studied, including 2 patients with both tests. Cases (N = 93) had angiographically significant stenosis (≥50% of left main or ≥ 70% of an epicardial coronary artery ≥2 mm in diameter); controls (N = 44) did not. TWH, i.e., interlead splay of T waves, was determined by second central moment analysis from precordial leads by an investigator blinded to angiographic results.

RESULTS

At rest, TWH levels were similar for cases and controls. ETT and dipyridamole stress testing increased TWH by 69% (p < 0.0001) and 27% (p < 0.0001), respectively, in cases. In controls, TWH did not change. Areas under the ROC curves for TWH increase for any flow-limiting coronary artery stenosis were 0.737 (p < 0.0001) for ETT and 0.818 (p < 0.0001) for dipyridamole stress testing. By contrast, neither ST-segment changes during ETT (p = 0.12) nor MPI during dipyridamole stress testing (p = 0.60) discriminated cases from controls.

CONCLUSIONS

TWH measurement is a novel method that improves detection of angiographically confirmed flow-limiting stenoses in large epicardial coronary arteries during both ETT and MPI during pharmacologic stress testing with dipyridamole.

Optimal ECG Lead System for Exercise Assessment of Ischemic Heart Disease

The diagnostic value of an ECG exercise test in diagnosis of ischemic heart disease (IHD) is limited. We investigated whether it is possible to develop a method for diagnosis of IHD which uses a low number of optimal ECG leads and has a higher diagnostic efficiency than conventional exercise ECG. This study was carried out on 43 patients. The 67-lead high-resolution ECG was recorded at rest and during exercise. The diagnostic value of ST segment depression (ΔST60) and T-wave morphology change (δT) determined in optimized ECG lead configurations was higher than for the standard 12-lead ECG. The best results were obtained for δT determined from 6 ECG electrode locations where sensitivity and specificity were 70% and 69% whereas for the standard exercise ECG were 63% and 62%, respectively. The small number of ECG leads used allows for easy hardware implementation of the methods for use in clinical settings.

Assessment of trazodone-induced cardiotoxicity after repeated doses in rats

Trazodone (TRZ) is an antidepressant drug commonly used in the treatment of depression, anxiety, and insomnia. Although some studies demonstrated the adverse effects of TRZ related to cardiovascular system, the conflicting results were observed in these studies. Therefore, we aimed to investigate the cardiac adverse effects of TRZ in rats at repeated doses in our study. In accordance with this purpose, TRZ was administered orally to rats at 5, 10, and 20 mg/kg doses for 28 days. Electrocardiogram records, serum aspartate aminotransferase (AST), lactate dehydrogenase, creatine kinase-myoglobin band, cardiac troponin-T (cTn-T) levels, DNA damage in cardiomyocytes, and histologic view of heart tissues were evaluated. In addition, glutathione (GSH) and malondialdehyde (MDA) levels were measured to determine the oxidative status of cardiac tissue after TRZ administration. Heart rate was decreased, PR interval was prolonged, and QRS and T amplitudes were decreased in 20 mg/kg TRZ-administered group compared to the control group. Serum AST and cTn-T levels were significantly increased in 10 and 20 mg/kg TRZ-administered rats with respect to control rats. DNA damage was significantly increased in these groups. Additionally, degenerative histopathologic findings were observed in TRZ-administered groups. Although there was no difference in MDA levels between groups, GSH levels were significantly decreased in 10 and 20 mg/kg TRZ-administered groups compared to the control group. Our results have shown that TRZ induced cardiotoxicity in rats dose-dependently. It is assumed that oxidative stress related to GSH depletion may be accompanied by these adverse effects.

Perspectives of human verification via binary QRS template matching of single-lead and 12-lead electrocardiogram

Objective

This study aims to validate the 12-lead electrocardiogram (ECG) as a biometric modality based on two straightforward binary QRS template matching characteristics. Different perspectives of the human verification problem are considered, regarding the optimal lead selection and stability over sample size, gender, age, heart rate (HR).

Methods

A clinical 12-lead resting ECG database, including a population of 460 subjects with two-session recordings (>1 year apart) is used. Cost-effective strategies for extraction of personalized QRS patterns (100ms) and binary template matching estimate similarity in the time scale (matching time) and dissimilarity in the amplitude scale (mismatch area). The two-class person verification task, taking the decision to validate or to reject the subject identity is managed by linear discriminant analysis (LDA). Non-redundant LDA models for different lead configurations (I,II,III,aVF,aVL,aVF,V1-V6) are trained on the first half of 230 subjects by stepwise feature selection until maximization of the area under the receiver operating characteristic curve (ROC AUC). The operating point on the training ROC at equal error rate (EER) is tested on the independent dataset (second half of 230 subjects) to report unbiased validation of test-ROC AUC and true verification rate (TVR = 100-EER). The test results are further evaluated in groups by sample size, gender, age, HR.

Results and discussion

The optimal QRS pattern projection for single-lead ECG biometric modality is found in the frontal plane sector (60°-0°) with best (Test-AUC/TVR) for lead II (0.941/86.8%) and slight accuracy drop for -aVR (-0.017/-1.4%), I (-0.01/-1.5%). Chest ECG leads have degrading accuracy from V1 (0.885/80.6%) to V6 (0.799/71.8%). The multi-lead ECG improves verification: 6-chest (0.97/90.9%), 6-limb (0.986/94.3%), 12-leads (0.995/97.5%). The QRS pattern matching model shows stable performance for verification of 10 to 230 individuals; insignificant degradation of TVR in women by (1.2–3.6%), adults ≥70 years (3.7%), younger <40 years (1.9%), HR<60bpm (1.2%), HR>90bpm (3.9%), no degradation for HR change (0 to >20bpm).

Distinct ECG Phenotypes Identified in Hypertrophic Cardiomyopathy Using Machine Learning Associate With Arrhythmic Risk Markers

Aims: Ventricular arrhythmia triggers sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM), yet electrophysiological biomarkers are not used for risk stratification. Our aim was to identify distinct HCM phenotypes based on ECG computational analysis, and characterize differences in clinical risk factors and anatomical differences using cardiac magnetic resonance (CMR) imaging.

Methods: High-fidelity 12-lead Holter ECGs from 85 HCM patients and 38 healthy volunteers were analyzed using mathematical modeling and computational clustering to identify phenotypic subgroups. Clinical features and the extent and distribution of hypertrophy assessed by CMR were evaluated in the subgroups.

Results: QRS morphology alone was crucial to identify three HCM phenotypes with very distinct QRS patterns. Group 1 (n = 44) showed normal QRS morphology, Group 2 (n = 19) showed short R and deep S waves in V4, and Group 3 (n = 22) exhibited short R and long S waves in V4-6, and left QRS axis deviation. However, no differences in arrhythmic risk or distribution of hypertrophy were observed between these groups. Including T wave biomarkers in the clustering, four HCM phenotypes were identified: Group 1A (n = 20), with primary repolarization abnormalities showing normal QRS yet inverted T waves, Group 1B (n = 24), with normal QRS morphology and upright T waves, and Group 2 and Group 3 remaining as before, with upright T waves. Group 1A patients, with normal QRS and inverted T wave, showed increased HCM Risk-SCD scores (1A: 4.0%, 1B: 1.8%, 2: 2.1%, 3: 2.5%, p = 0.0001), and a predominance of coexisting septal and apical hypertrophy (p < 0.0001). HCM patients in Groups 2 and 3 exhibited predominantly septal hypertrophy (85 and 90%, respectively).

Conclusion: HCM patients were classified in four subgroups with distinct ECG features. Patients with primary T wave inversion not secondary to QRS abnormalities had increased HCM Risk-SCD scores and coexisting septal and apical hypertrophy, suggesting that primary T wave inversion may increase SCD risk in HCM, rather than T wave inversion secondary to depolarization abnormalities. Computational ECG phenotyping provides insight into the underlying processes captured by the ECG and has the potential to be a novel and independent factor for risk stratification.

Data Driven Computer Simulation to Analyse an ECG Limb Lead System Used in Connected Health Environments

Background: Recently under the Connected Health initiative, researchers and small-medium engineering companies have developed Electrocardiogram (ECG) monitoring devices that incorporate non-standard limb electrode positions, which we have named the Central Einthoven (CE) configuration.

Objectives: The main objective of this study is to compare ECG signals recorded from the CE configuration with those recorded from the recommended Mason-Likar (ML) configuration.

Methods: This study involved extracting two different sets of ECG limb leads from each patient to compare the difference in the signals. This was done using computer simulation that is driven by body surface potential maps. This simulator was developed to facilitate this experiment but it can also be used to test similar hypotheses. This study included, (a) 176 ECGs derived using the ML electrode positions and (b) the 176 corresponding ECGs derived using the CE electrode positions. The signals from these ECGs were compared using root mean square error (RMSE), Pearson product-moment correlation coefficient (r) and similarity coefficient (SC). We also investigated whether the CE configuration influences the calculated mean cardiac axis. The top 10 cases where the ECGs were significantly different between the two configurations were visually compared by an ECG interpreter.

Results: We found that the leads aVL, III and aVF are most affected when using the CE configuration. The absolute mean difference between the QRS axes from both configurations was 28° (SD = 37°). In addition, we found that in 82% of the QRS axes calculated from the CE configuration was more rightward in comparison to the QRS axes derived from the ML configuration. Also, we found that there is an 18% chance that a misleading axis will be located in the inferior right quadrant when using the CE approach. Thus, the CE configuration can emulate right axis deviation. The clinician visually identified 6 out of 10 cases where the CE based ECG yielded clinical differences that could result in false positives.

Conclusions: The CE configuration will not yield the same diagnostic accuracy for diagnosing pathologies that rely on current amplitude criteria. Conversely, rhythm lead II was not significantly affected, which supports the use of the CE approach for assessing cardiac rhythm only. Any computerised analysis of the CE based ECG will need to take these findings into consideration.

Accuracy in precordial ECG lead placement: Improving performance through a peer-led educational intervention

BACKGROUND AND OBJECTIVES

Inaccurate electrocardiography (ECG) lead placement may lead to erroneous diagnoses, such as poor R wave progression. We sought to assess the accuracy of precordial ECG lead placement amongst hospital staff members, and to re-evaluate performance after an educational intervention.

METHODS AND RESULTS

100 randomly selected eligible staff members placed sticker dots on a mannequin, their positions were recorded on a radar plot and compared to the correct precordial lead positions. The commonest errors were placing V1 and V2 leads too superiorly, and V5 and V6 leads too medially.Following an educational intervention with the aid of moderated poster presentations and volunteer patients, the study was repeated six months later. 60 subjects correctly placed all leads, compared to 10 in the pre-intervention cohort (P<0.0001) with the proportion achieving correct placement of any lead rising from 0.34 to 0.83, (p<0.0001 for all leads).

CONCLUSION

Incorrect ECG lead placement is common. This may be addressed through regular training incorporated into annual induction processes for relevant health care professionals.

Significance of a negative sinus P wave in lead V2 of the clinical electrocardiogram

BACKGROUND

A negative sinus P wave in lead V₂ (NPV₂ ) of the electrocardiogram (ECG) is rare when leads are positioned correctly. This study was undertaken to clarify the significance of an unusually high incidence of this anomaly found in ECGs at my institution.

METHODS

One thousand four hundred thirty-five ECGs were randomly selected to determine the incidence and gender frequency in tracings showing positive (PPV₂ ), and biphasic (BPV₂ ) P waves in V₂ , as well as NPV₂ . To those cases with NPV₂ , 84 cases with that anomaly from earlier archived ECGs were added to give a larger group for analysis. Medical records were reviewed for clinical details and other archived ECGs.

RESULTS

PPV₂ , BPV₂ , and NPV₂ were found in 1,216 (84.5%), 150 (10.5%), and 69 cases (4.8%), respectively. Cases with NPV₂ were more likely to be female (46 of 69 or 67.7%) than were those with either PPV₂ (500 of 1,216 or 41.1%; p < .001), or BPV₂ (71 of 150 or 47.3%; p < .01). NPV₂ was commonly associated with ECG findings of left atrial abnormality (LAA), septal myocardial infarction, or a ventricular repolarization abnormality, but when multiple ECGs were available in these cases, such abnormalities were usually absent when there was either PPV₂ or BPV₂ .

CONCLUSIONS

With correct precordial lead placement, NPV₂ is rare and BPV₂ is also uncommon, and their presence should alert one to the probability of high placement of V₁ and V₂ , which can produce ECGs that mimic LAA, septal infarction, and ventricular repolarization abnormality.

Improving Accuracy of Cardiac Electrode Placement: Outcomes of Clinical Nurse Specialist Practice

PURPOSE

The purpose of this quality improvement project was to facilitate a sustainable improvement in the accuracy of cardiac electrode placement for continuous bedside monitoring in intensive care unit patients.

BACKGROUND

Continuous cardiac electrocardiograph monitoring is a standard of practice in critical care areas and is essential to accurate interpretation of cardiac dysrhythmias and early detection of myocardial ischemia. Accurate assessment of electrocardiographs depends on precise placement of electrodes; however, electrodes are often placed inaccurately.

RATIONALE

Evaluation of baseline practice revealed that cardiac electrodes were placed correctly in only 12.5% of patients. The most frequently misplaced electrode was the V lead, followed by lower limb leads.

DESCRIPTION

This project was conducted between July 1, 2013, and October 31, 2013, and involved a multifaceted education program for registered nurse and patient care technician staff on the physiologic basis and technical procedures for cardiac electrode placement. The clinical nurse specialist served as an informal leader, role model, and mentor by developing and empowering unit champions to perform real-time auditing and provide real-time feedback to colleagues.

OUTCOME

At 3 months after intervention, the accuracy of cardiac electrode placement was sustained at greater than 85%, representing a 6-fold improvement above the preintervention baseline.

CONCLUSION

Sustainable improvement in quality requires creation of a culture that supports quality improvement initiatives. As experts in clinical practice, evidence-based practice, and leadership, clinical nurse specialists are optimally positioned to function as change agents whose initiatives measurably improve outcomes.

IMPLICATIONS

This quality improvement project serves as a model for improving accuracy of cardiac electrode placement at the nursing staff level. Future research is necessary to improve outcomes related to accuracy of cardiac electrode placement on the patient and systems levels.

Inter-lead correlation analysis for automated detection of cable reversals in 12/16-lead ECG

BACKGROUND AND OBJECTIVE

A crucial factor for proper electrocardiogram (ECG) interpretation is the correct electrode placement in standard 12-lead ECG and extended 16-lead ECG for accurate diagnosis of acute myocardial infarctions. In the context of optimal patient care, we present and evaluate a new method for automated detection of reversals in peripheral and precordial (standard, right and posterior) leads, based on simple rules with inter-lead correlation dependencies.

METHODS

The algorithm for analysis of cable reversals relies on scoring of inter-lead correlations estimated over 4s snapshots with time-coherent data from multiple ECG leads. Peripheral cable reversals are detected by assessment of nine correlation coefficients, comparing V6 to limb leads: (I, II, III, -I, -II, -III, -aVR, -aVL, -aVF). Precordial lead reversals are detected by analysis of the ECG pattern cross-correlation progression within lead sets (V1-V6), (V4R, V3R, V3, V4), and (V4, V5, V6, V8, V9). Disturbed progression identifies the swapped leads.

RESULTS

A test-set, including 2239 ECGs from three independent sources-public 12-lead (PTB, CSE) and proprietary 16-lead (Basel University Hospital) databases-is used for algorithm validation, reporting specificity (Sp) and sensitivity (Se) as true negative and true positive detection of simulated lead swaps. Reversals of limb leads are detected with Se = 95.5-96.9% and 100% when right leg is involved in the reversal. Among all 15 possible pairwise reversals in standard precordial leads, adjacent lead reversals are detected with Se = 93.8% (V5-V6), 95.6% (V2-V3), 95.9% (V3-V4), 97.1% (V1-V2), and 97.8% (V4-V5), increasing to 97.8-99.8% for reversals of anatomically more distant electrodes. The pairwise reversals in the four extra precordial leads are detected with Se = 74.7% (right-sided V4R-V3R), 91.4% (posterior V8-V9), 93.7% (V4R-V9), and 97.7% (V4R-V8, V3R-V9, V3R-V8). Higher true negative rate is achieved with Sp > 99% (standard 12-lead ECG), 81.9% (V4R-V3R), 91.4% (V8-V9), and 100% (V4R-V9, V4R-V8, V3R-V9, V3R-V8), which is reasonable considering the low prevalence of lead swaps in clinical environment.

CONCLUSIONS

Inter-lead correlation analysis is able to provide robust detection of cable reversals in standard 12-lead ECG, effectively extended to 16-lead ECG applications that have not previously been addressed.

Human factors analysis of the CardioQuick Patch®: A novel engineering solution to the problem of electrode misplacement during 12-lead electrocardiogram acquisition

INTRODUCTION

The CardioQuick Patch® (CQP) has been developed to assist operators in accurately positioning precordial electrodes during 12-lead electrocardiogram (ECG) acquisition. This study describes the CQP design and assesses the device in comparison to conventional electrode application.

METHODS

Twenty ECG technicians were recruited and a total of 60 ECG acquisitions were performed on the same patient model over four phases: (1) all participants applied single electrodes to the patient; (2) all participants were then re-trained on electrode placement and on how to use the CQP; (3) participants were randomly divided into two groups, the standard group applied single electrodes and the CQP group used the CQP; (4) after a one day interval, the same participants returned to carry out the same procedure on the same patient (measuring intra-practitioner variability). Accuracy was measured with reference to pre-marked correct locations using ultra violet ink. NASA-TLK was used to measure cognitive workload and the Systematic Usability Scale (SUS) was used to quantify the usability of the CQP.

RESULTS

There was a large difference between the minimum time taken to complete each approach (CQP=38.58s vs. 65.96s). The standard group exhibited significant levels of electrode placement error (V1=25.35mm±29.33, V2=18.1mm±24.49, V3=38.65mm±15.57, V4=37.73mm±12.14, V5=35.75mm±15.61, V6=44.15mm±14.32). The CQP group had statistically greater accuracy when placing five of the six electrodes (V1=6.68mm±8.53 [p<0.001], V2=8.8mm±9.64 [p=0.122], V3=6.83mm±8.99 [p<0.001], V4=14.90mm±11.76 [p<0.001], V5=8.63mm±10.70 [p<0.001], V6=18.13mm±14.37 [p<0.001]). There was less intra-practitioner variability when using the CQP on the same patient model. NASA TLX revealed that the CQP did increase the cognitive workload (CQP group=16.51%±8.11 vs. 12.22%±8.07 [p=0.251]). The CQP also achieved a high SUS score of 91±7.28.

CONCLUSION

The CQP significantly improved the reproducibility and accuracy of placing precordial electrodes V1, V3-V6 with little additional cognitive effort, and with a high degree of usability.

Novel Bloodless Potassium Determination Using a Signal-Processed Single-Lead ECG

BACKGROUND

Hyper- and hypokalemia are clinically silent, common in patients with renal or cardiac disease, and are life threatening. A noninvasive, unobtrusive, blood-free method for tracking potassium would be an important clinical advance.

METHODS AND RESULTS

Two groups of hemodialysis patients (development group, n=26; validation group, n=19) underwent high-resolution digital ECG recordings and had 2 to 3 blood tests during dialysis. Using advanced signal processing, we developed a personalized regression model for each patient to noninvasively calculate potassium values during the second and third dialysis sessions using only the processed single-channel ECG. In addition, by analyzing the entire development group's first-visit data, we created a global model for all patients that was validated against subsequent sessions in the development group and in a separate validation group. This global model sought to predict potassium, based on the T wave characteristics, with no blood tests required. For the personalized model, we successfully calculated potassium values with an absolute error of 0.36±0.34 mmol/L (or 10% of the measured blood potassium). For the global model, potassium prediction was also accurate, with an absolute error of 0.44±0.47 mmol/L for the training group (or 11% of the measured blood potassium) and 0.5±0.42 for the validation set (or 12% of the measured blood potassium).

CONCLUSIONS

The signal-processed ECG derived from a single lead can be used to calculate potassium values with clinically meaningful resolution using a strategy that requires no blood tests. This enables a cost-effective, noninvasive, unobtrusive strategy for potassium assessment that can be used during remote monitoring.

Unusual QRS Pattern in the Early Precordial Leads

An asymptomatic, middle-aged man is found to have a QR pattern in lead V1 and a qR pattern in lead V2 of his ECG obtained during routine life insurance applicant screening. The risk assessment implication of this ECG finding is reviewed.

Telemedicine supported by Augmented Reality: an interactive guide for untrained people in performing an ECG test

BACKGROUND

In many telemedicine applications, the correct use of medical device at the point of need is essential to provide an appropriate service. Some applications may require untrained people to interact with medical devices and patients: care delivery in transportation, military actions, home care and telemedicine training.Appropriate operation of medical device and correct connection with patient's body are crucial. In these scenarios, tailored applications of Augmented Reality can offer a valid support by guiding untrained people at the point of need. This study aims to explore the feasibility of using Augmented Reality in telemedicine applications, by facilitating an acceptable use of biomedical equipment by any unskilled person. In particular, a prototype system was built in order to estimate how untrained users, with limited or no knowledge, can effectively interact with an ECG device and properly placing ECG electrodes on patient's chest.

METHODS

An Augmented Reality application was built to support untrained users in performing an ECG test. Simple markers attached to the ECG device and onto patient's thorax allow camera calibration. Once objects and their pose in the space are recognized, the video of the current scene is enriched, in real-time, with additional pointers, text boxes and audio that help the untrained operator to perform the appropriate sequence of operations. All the buttons, switches, ports of the ECG device together with the location of precordial leads were coded and indicated. Some user's voice commands were also included to improve usability.

RESULTS

Ten untrained volunteers, supported by the augmented reality, were able to carry out a complete ECG test first on a mannequin and then on a real patient in a reasonable time (about 8 minutes on average). Average positioning errors of precordial electrodes resulted less than 3 mm for the mannequin and less than 7 mm for the real patient. These preliminary findings suggest the effectiveness of the developed application and the validity of clinical ECG recordings.

CONCLUSION

This application can be adapted to support the use of other medical equipment as well as other telemedicine tasks and it could be performed with a Tablet or a Smartphone.