Combination Of Electrocardiography Research Articles

Robust in-vehicle heartbeat detection using multimodal signal fusion

A medical check-up during driving enables the early detection of diseases. Heartbeat irregularities indicate possible cardiovascular diseases, which can be determined with continuous health monitoring. Therefore, we develop a redundant sensor system based on electrocardiography (ECG) and photoplethysmography (PPG) sensors attached to the steering wheel, a red, green, and blue (RGB) camera behind the steering wheel. For the video, we integrate the face recognition engine SeetaFace to detect landmarks of face segments continuously. Based on the green channel, we derive colour changes and, subsequently, the heartbeat. We record the ECG, PPG, video, and reference ECG with body electrodes of 19 volunteers during different driving scenarios, each lasting 15 min: city, highway, and countryside. We combine early, signal-based late, and sensor-based late fusion with a hybrid convolutional neural network (CNN) and integrated majority voting to deliver the final heartbeats that we compare to the reference ECG. Based on the measured and the reference heartbeat positions, the usable time was 51.75%, 58.62%, and 55.96% for the driving scenarios city, highway, and countryside, respectively, with the hybrid algorithm and combination of ECG and PPG. In conclusion, the findings suggest that approximately half the driving time can be utilised for in-vehicle heartbeat monitoring.

Accessory pathway analysis using a multimodal deep learning model

Cardiac accessory pathways (APs) in Wolff–Parkinson–White (WPW) syndrome are conventionally diagnosed with decision tree algorithms; however, there are problems with clinical usage. We assessed the efficacy of the artificial intelligence model using electrocardiography (ECG) and chest X-rays to identify the location of APs. We retrospectively used ECG and chest X-rays to analyse 206 patients with WPW syndrome. Each AP location was defined by an electrophysiological study and divided into four classifications. We developed a deep learning model to classify AP locations and compared the accuracy with that of conventional algorithms. Moreover, 1519 chest X-ray samples from other datasets were used for prior learning, and the combined chest X-ray image and ECG data were put into the previous model to evaluate whether the accuracy improved. The convolutional neural network (CNN) model using ECG data was significantly more accurate than the conventional tree algorithm. In the multimodal model, which implemented input from the combined ECG and chest X-ray data, the accuracy was significantly improved. Deep learning with a combination of ECG and chest X-ray data could effectively identify the AP location, which may be a novel deep learning model for a multimodal model.

Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram.

A new algorithm based on singular value decomposition (SVD) to remove cardiac contamination from trunk electromyography (EMG) is proposed. Its performance is compared to currently available algorithms at different signal-to-noise ratios (SNRs). The algorithm is applied on individual channels. An experimental calibration curve to adjust the number of SVD components to the SNR (0–20 dB) is proposed. A synthetic dataset is generated by the combination of electrocardiography (ECG) and EMG to establish a ground truth reference for validation. The performance is compared with state-of-the-art algorithms: gating, high-pass filtering, template subtraction (TS), and independent component analysis (ICA). Its applicability on real data is investigated in an illustrative diaphragm EMG of a patient with sleep apnea. The SVD-based algorithm outperforms existing methods in reconstructing trunk EMG. It is superior to the others in the time (relative mean squared error < 15%) and frequency (shift in mean frequency < 1 Hz) domains. Its feasibility is proven on diaphragm EMG, which shows a better agreement with the respiratory cycle (correlation coefficient = 0.81, p-value < 0.01) compared with TS and ICA. Its application on real data is promising to non-obtrusively estimate respiratory effort for sleep-related breathing disorders. The algorithm is not limited to the need for additional reference ECG, increasing its applicability in clinical practice.

Diagnostic approach for myocardial contusion: a retrospective evaluation of patient data and review of the literature

PurposeMyocardial contusion can be a life-threatening condition in patients who sustained blunt thoracic trauma. The diagnostic approach remains a subject of debate. The aim of this study was to determine the sensitivity and specificity of echocardiography, electrocardiography, troponins T and I (TnT and TnI), and creatine kinase muscle/brain (CK-MB) for identifying patients with a myocardial contusion following blunt thoracic trauma.MethodsSensitivity and specificity were first determined in a 10-year retrospective cohort study and second by a systematic literature review with meta-analysis.ResultsOf the 117 patients in the retrospective study, 44 (38%) were considered positive for myocardial contusion. Chest X-ray, chest CT scan, electrocardiograph, and echocardiography had poor sensitivity (< 15%) but good specificity (≥ 90%). Sensitivity to cardiac biomarkers measured at presentation ranged from 59% for TnT to 77% for hs-TnT, specificity ranged from 63% for CK-MB to 100% for TnT. The systematic literature review yielded 28 studies, with 14.5% out of 7242 patients reported as positive for myocardial contusion. The pooled sensitivity of electrocardiography, troponin I, and CK-MB was between 62 and 71%, versus only 45% for echocardiography and 38% for troponin T. The pooled specificity ranged from 63% for CK-MB to 85% for troponin T and 88% for echocardiography.ConclusionThe best diagnostic approach for myocardial contusion is a combination of electrocardiography and measurement of cardiac biomarkers. If abnormalities are found, telemonitoring is necessary for the early detection of life-threatening arrhythmias. Chest X-ray and CT scan may show other thoracic injuries but provide no information on myocardial contusion.

Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging.

Quantitative cardiovascular magnetic resonance (CMR) imaging can be used to characterize fibrosis, oedema, ischaemia, inflammation and other disease conditions. However, the need to reduce artefacts arising from body motion through a combination of electrocardiography (ECG) control, respiration control, and contrast-weighting selection makes CMR exams lengthy. Here, we show that physiological motions and other dynamic processes can be conceptualized as multiple time dimensions that can be resolved via low-rank tensor imaging, allowing for motion-resolved quantitative imaging with up to four time dimensions. This continuous-acquisition approach, which we name cardiovascular MR multitasking, captures — rather than avoids — motion, relaxation and other dynamics to efficiently perform quantitative CMR without the use of ECG triggering or breath holds. We demonstrate that CMR multitasking allows for T1 mapping, T1-T2 mapping and time-resolved T1 mapping of myocardial perfusion without ECG information and/or in free-breathing conditions. CMR multitasking may provide a foundation for the development of setup-free CMR imaging for the quantitative evaluation of cardiovascular health.

An Adaptive Seismocardiography (SCG)-ECG Multimodal Framework for Cardiac Gating Using Artificial Neural Networks.

To more accurately trigger data acquisition and reduce radiation exposure of coronary computed tomography angiography (CCTA), a multimodal framework utilizing both electrocardiography (ECG) and seismocardiography (SCG) for CCTA prospective gating is presented. Relying upon a three-layer artificial neural network that adaptively fuses individual ECG- and SCG-based quiescence predictions on a beat-by-beat basis, this framework yields a personalized quiescence prediction for each cardiac cycle. This framework was tested on seven healthy subjects (age: 22-48; m/f: 4/3) and eleven cardiac patients (age: 31-78; m/f: 6/5). Seventeen out of 18 benefited from the fusion-based prediction as compared to the ECG-only-based prediction, the traditional prospective gating method. Only one patient whose SCG was compromised by noise was more suitable for ECG-only-based prediction. On average, our fused ECG-SCG-based method improves cardiac quiescence prediction by 47% over ECG-only-based method; with both compared against the gold standard, B-mode echocardiography. Fusion-based prediction is also more resistant to heart rate variability than ECG-only- or SCG-only-based prediction. To assess the clinical value, the diagnostic quality of the CCTA reconstructed volumes from the quiescence derived from ECG-, SCG- and fusion-based predictions were graded by a board-certified radiologist using a Likert response format. Grading results indicated the fusion-based prediction improved diagnostic quality. ECG may be a sub-optimal modality for quiescence prediction and can be enhanced by the multimodal framework. The combination of ECG and SCG signals for quiescence prediction bears promise for a more personalized and reliable approach than ECG-only-based method to predict cardiac quiescence for prospective CCTA gating.

Add-on tests for improving risk-stratification in emergency department patients with chest pain who are at low to moderate risk of 30-day major adverse cardiac events

BackgroundChest pain patients commonly present to emergency departments (ED), and require either hospital admission and/or lengthy diagnostic protocols to rule-out myocardial infarction. We aimed to identify the best combination of add-on tests to high-sensitivity cardiac troponin (hs-cTnT) for predicting 30-day major adverse cardiac events (MACE) in adult chest pain patients presenting to an ED with suspected acute coronary syndrome. MethodsThis prospective observational study was conducted in the ED of a tertiary university hospital in Hong Kong, recruiting adult patients with chest pain of less than 24h duration, suspected with acute coronary syndrome (ACS), and had no history of coronary artery bypass grafting or stent insertion. Patients underwent triage assessment, electrocardiography, blood sampling for laboratory hs-cTnT, and Thrombolysis in Myocardial Infarction (TIMI) and HEART score assessment. The primary outcome was the number of patients with 30-day MACE. Results602 consecutive patients were recruited and completed 30-day follow-up. A 30-day MACE occurred in 42 (7.0%) patients. Out of 12 possible models for stratifying patients at risk of 30-day MACE within 2h of ED arrival, a combination of electrocardiography (ECG) and one-time hs-cTnT (model 5) provided the simplest and most accurate model. A risk score of 0 to 5 was derived from raw coefficients of model 5. The risk score provided excellent calibration (P=0.91) and discrimination (AUC 0.87, 95% CI: 0.82 to 0.93). ConclusionAppropriate early risk-stratification of patients with chest pain and possible ACS using a combination of ECG and one-time hs-cTnT may improve efficiency of care.

Arrhythmogenic right ventricular cardiomyopathy associated ventricular tachycardia misdiagnosed as idiopathic right ventricular outflow tract origin and its management

Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) is an autosomal dominant genetic form of cardiomyopathy (CM), which primarily affects the right ventricle (RV) and results in life threatening ventricular arrhythmias and sudden cardiac death (SCD). Diagnosis is difficult due to the broad spectrum of phenoltypic variations, especially in the early stage. Clinical suspicion should be raised in the setting of refractory ventricular tachycardia originating from the RV, and the final diagnosis could be made based on the combination of electrocardiography, echocardiography, cardiac magnetic resonance imaging (CMRI) and myocardial biopsy. Implantable cardioverter-defibrillator (ICD) implantation is an effective option for the treatment of ARVC.

Accuracy of Preoperative Electrocardiographic and Chest Radiographic Screening for Prediction of Left Ventricular Dysfunction in Patients with Suspected Neuromuscular Disorders

We sought to determine the reliability of electrocardiography (ECG) and chest radiography (CXR) in predicting left ventricular (LV) dysfunction in patients with suspected neuromuscular disorders (NMDs) undergoing preanesthetic evaluation for muscle biopsy. In this retrospective study, 255 patients with a preliminary diagnosis of NMDs based on history, physical examination, and laboratory testing underwent preanesthetic screening before muscle biopsy. The screening included various combinations of ECG, CXR, and transthoracic echocardiography (Echo) to assess perioperative risk associated with potentially undiagnosed LV dysfunction. Multivariate logistic regression analysis was applied to ascertain whether CXR and ECG were independently predictive of LV dysfunction. In addition, receiver-operating characteristic curve analysis was used to assess the diagnostic accuracy of each test and the combination of CXR and ECG in differentiating LV dysfunction from normal function based on Echo "gold standard" data. The study consisted of 255 patients who had a transthoracic Echo, and among these patients, 235 had CXR and 237 had ECG. Forty-four patients were diagnosed by transthoracic Echo to have LV dysfunction (17.3%). Of the 255 patients in the study population, 24 were found to have mild LV dysfunction (9.4%) and 20 had moderate to severe LV dysfunction (7.8%) on Echo. With Echo providing the definitive standard for the diagnosis of LV dysfunction, we found that a CXR alone was predictive in 37% of cases of LV dysfunction, an ECG alone was predictive in 14% of cases, and the combination of both was predictive in 81% of cases. The combination of ECG and CXR test offered the highest diagnostic accuracy (area under the curve of 0.95, P < 0.0001) for differentiating moderate to severe LV dysfunction from normal LV function. In patients with suspected neuromuscular disease, CXR and ECG provided low independent diagnostic prediction for the presence or absence of LV dysfunction. The combination of both tests can identify cardiomyopathy with relatively high accuracy in children with suspected NMDs independent of age and gender, particularly in patients with moderate to severe LV dysfunction. Although our findings suggest that combination ECG and CXR screening is a reliable means of detecting LV dysfunction, this approach fails to differentiate the severity or type of cardiomyopathy that may exist. Therefore, the decision to obtain a perioperative Echo before muscle biopsy should involve careful consideration of the disease suspected, ECG and CXR results, laboratory studies, patient age, physical examination, and family history.

Prediction of 2-year outcome by combining TIMI myocardial perfusion grading with sum ST segment resolution in patients with acute myocardial infarction

To evaluate the value of combining TIMI myocardial perfusion (TMP) grading with sum ST segment resolution (sumSTR) in prediction of the 2-year outcome and heart function in patients with acute myocardial infarction (AMI) after emergency percutaneous intervention (PCI). Seventy-seven consecutive patients of AMI with elevated ST segment, 62 males and 15 females, aged 63 +/- 12 (30-91), underwent PCI. TMP grading was used in combination of electrocardiography to calculate the sumSTR so as to evaluate the effect of myocardial reperfusion. The patients with TMP grade 2-3 and sumSTR > or = 30% were included in the group of better perfusion, and those with the TMP grade 0-1 and sumSTR < 30% were included in the group of lower perfusion. The cardiac events, including death, reinfarction, revascularization, angina pectoris, and heart failure were recorded. The left ventricular end-diastolic dimension (LVEDD) and left ventricular ejection fraction (LVEF) were measured by echocardiography 72 hours and 2 years after the PCI. There were 37 patients in the lower perfusion group and 39 patients in the better perfusion group. Cos regression showed that TMP grade 0-1 associated with sumSTR < 30% was an independent factor for 2-year cardiac events (RR = 13.186, 95% CI 2.149 - 80.917, P = 0.005). The LVEDD 2 years after PCI was 60 mm +/- 4 mm, significantly higher than that 72 hours after PCI (53 mm +/- 4 mm. P < 0.01) in the lower perfusion group. The LVEDD increased by 7.1 mm +/- 1.9 mm two years after PCI in the lower perfusion group, significantly more than that in the better perfusion group (1.5 mm +/- 1.2 mm, P < 0.01). The myocardial perfusion after PCI was closely correlated with the extent of heart function improvement 2 years after (chi(2) = 50.58, P < 0.01). TMP grading combined with sumSTR helps predict the 2-year outcome and heart function in the patients with AMI after emergency PCI.

Noninvasive Diagnosis of Coronary Artery Disease: A Comparison between Cardiokymographic and Electrocardiographic Stress Testing

Noninvasive cardiokymography has been further developed to be able to record wall motion abnormalities during exercise. The study was designed to evaluate the diagnostic accuracy of stress cardiokymography and electrocardiography in the diagnosis of coronary artery disease. 223 patients were included in a prospective investigation using a newly developed computerized cardiokymography device. Sensitivity, specificity, and positive predictive value were 61, 69 and 90% for exercise cardiokymography, and 57, 74 and 91% for exercise electrocardiography, respectively. There was no statistically significant difference between cardiokymography and electrocardiography. The combination of electrocardiography and cardiokymography did not produce a significant improvement in diagnostic accuracy in comparison to exercise electrocardiography alone.

Noninvasive Estimates of Cardiac Performance during and Early after Single and Repeated Passive Upright Tilt in Normal Men: Volume Dependency of Systolic Time Intervals and Maximum Velocity of Transthoracic Impedance Changes

The combination of electrocardiography, impedance cardiography and phonocardiography allows to measure systolic time intervals and maximum velocity of transthoracic impedance changes (dZ/dt(max)) as estimates of (changes in) cardiac performance. Such assessment was performed in 35 normal male subjects undergoing single gradual passive upright tilting and 11 subjects undergoing repeated upright tilting. During tilting a cardio-acceleratory and vasopressor response is evident in compensation for the largely reduced stroke volume as a consequence of the reduced preload. During upright tilting, heart rate-corrected preejection pressure (PEP) was prolonged, heart rate-corrected left ventricular ejection time (LVET) was shortened and PEP/LVET was increased, and dZ/dt(max) and related parameters were reduced during upright tilting. These changes most likely reflect the preload dependency of these parameters even to such an extent that they could not reflect net inotropic changes related to the increased adrenergic activity during tilting. During the first 10 min after upright tilt, dZ/dt(max) and estimated stroke volume were increased versus supine baseline prior to tilt, whereas the return of the estimated thoracic blood volume back to baseline was delayed. This was associated with a relative bradycardia and slight reduction in diastolic blood pressure. These changes reached their maximum on average 3–4 min after the supine position was resumed. This enhanced cardiac pump performance early after tilt, suggested by dZ/dt(max) and related parameters, was not associated with corresponding changes in systolic time intervals. Although both systolic time intervals and dZ/dt(max) may be volumedependent, dZ/dt(max) and related parameters may offer additional information on cardiac performance not derivable from systolic time intervals.