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Computers in Cardiology (CinC)

作者： Richard E Gregg Eric D Helfenbein Sophia H Zhou Advanced Algorithm Research Center Philips Healthcare Andover MA USA

The bull's eye plot has been successfully introduced in multiple cardiac imaging diagnostic modalities and standardized by AHA in recent years. The ECG estimated myocardial infarct (MI) size is a quantitative measure of the size of the infarct region in left ventricular myocardium and is a proven tool to assist cardiologists in clinical decision making. MI size has been presented as a percentage of the left ventricle (LV) mass based on Selvester ECG scoring system. The scoring system has 50 ECG criteria with corresponding points. The reported MI size is not associated with a specific location in LV. This study applied the Selvester scoring system and bull's eye plot to create a quantitative MI size presentation with visual location in the LV. The automated Selvester scoring algorithm was validated using a database of 688 ECGs with and without MI. The automated ECG-MI size was tested against two cardiologists' manual scores resulting in 94% correlation.

关键词： Electrocardiography Myocardium Cardiology Visualization Image segmentation Heart

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An Ensemble of Bagged Decision Trees for Early Prediction of Sepsis

An Ensemble of Bagged Decision Trees for Early Prediction of...

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Computers in Cardiology (CinC)

作者： Reza Firoozabadi Saeed Babaeizadeh Advanced Algorithm Research Center Philips Healthcare Andover MA USA

ISBN: (数字)9781728169361

ISBN: (纸本)9781728159423

Sepsis is a serious medical condition caused by the body's response to an infection. Early prediction and treatment of sepsis are critical. In response to the PhysioNet/CinC Challenge 2019, we developed an algorithm for early prediction of sepsis. Three datasets provided by the challenge are from ICU patients in three separate hospitals, two of which are publicly available to the participants, but the third is hidden and used for scoring. Data are highly unbalanced and contain many missing values. Each patient's data comprises hourly collected samples of 40 features. We preprocessed the data by a plausibility filter eliminating the outliers, forward filling of the missing data and replacing the remaining by population mean, and standardization of the numerical data. We developed an ensemble of bagged decision trees with a highly unbalanced misclassification cost to predict the sepsis for each sample of features in a patient. The classifier was trained on the first hospital dataset and validated on the second hospital dataset. A total of 15 important features and a set of hyperparameters were selected in an iterative training approach. Our team (AlgTeam, ranking 39) submitted nine entries for evaluation on the subset of the hidden data and selected the entry with highest utility score which resulted in the final utility score of 0.24 on the full test dataset.

关键词： Hospitals Training Decision trees Classification algorithms Databases Prediction algorithms Sociology

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Modeling and Classification of the ST Segment Morphology for Enhanced Detection of Acute Myocardial Infarction

Modeling and Classification of the ST Segment Morphology for...

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Computers in Cardiology (CinC)

作者： Reza Firoozabadi Richard E Gregg Saeed Babaeizadeh Advanced Algorithm Research Center Philips Healthcare Andover MA USA

ISBN: (数字)9781728169361

ISBN: (纸本)9781728159423

A number of cardiac conditions such as acute pericarditis (PC) and early repolarization (ER) cause ST elevation which mimics ST-segment Elevation Myocardial Infarction (STEMI). Current guidelines recommend analyzing ST segment morphology to distinguish STEMI from these confounders. ST elevation in PC and ER (and possibly in STEMI) is concave (upward) in the JTpeak interval, while a convex or straight ECG ST segment is associated with the diagnosis of STEMI. We developed an algorithm to classify concavity characteristic of the ST segment. A quadratic polynomial regression algorithm was introduced to model the shape of JTpeak interval. Our diagnostic algorithm generated representative beats and measured the fiducial points and standard measurements such as ST level in 12-lead 10-sec segments of ECG recordings. JTpeak interval was modeled by a parabola using a least-squares polynomial regression algorithm. Classifier features such as curvature, parabola direction and vertex, model fit error, and the noise measure were determined. A bootstrap-aggregated tree ensemble classifier determined the ST segment shape. Our algorithm was evaluated on a 12-lead ECG database collected in two medical centers. Our ST segment polynomial regression model exhibited significant improvement in concavity detection versus a simple conventional method.

关键词： Electrocardiography Classification algorithms Myocardium Noise measurement Measurement uncertainty Databases Morphology

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Right precordial leads V4R and V5R in ECG detection of acute ST elevation MI associated with proximal right coronary artery occlusion

Right precordial leads V4R and V5R in ECG detection of acute...

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Computers in Cardiology, 2005

作者： Liu, X. Tragardh, E. Zhou, S.H. Pahlm, O. Startt-Selvester, R.H. Gregg, R.E. Helfenbein, E.D. Lindauer, J.M. Division of Cardiology Rui-Jin Hospital Shanghai Jiao-Tong University Shanghai China Department of Clinical Physiology Lund University Hospital Lund Sweden Advanced Algorithm Research Center Philips Medical Systems Thousand Oaks CA United States Long Beach Memorial Medical Center Long Beach CA United States Advanced Algorithm Research Center Philips Medical Systems 1525 Rancho Conejo Blvd. Thousand Oaks CA 91320

ISBN: (纸本)0780393376

ST elevation myocardial infarction (STEMI) in the right ventricle (RV) associated with right coronary artery (RCA) occlusion is known to have high hospital mortality. The hypothesis tested in this study is: right precordial leads V4R and V5R help detect STEMI in the right ventricle. ECGs from 1,970 subjects were collected in Ruijin Hospital (n =1,342), Shanghai, China and Lund University Hospital, Lund (n = 565), Sweden. All ECGs were recorded with additional leads on the right precordial location in V4R and V5R. Our results show that the subjects with middle to upper RCA occlusion often show ST elevation in leads V4R and V5R and ST depression in lateral leads I, aVL, V5-V6, and are often undetected as STEMI or AMI in the standard 12-lead ECG. We conclude that adding V4R and V5R to standard ECG recording in assessing patients presenting with acute coronary syndrome is an easy and convenient way to increases the sensitivity of STEMI detection. © 2005 IEEE.

关键词： Cardiology

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An automated algorithm for the detection of atrial fibrillation in the presence of paced rhythms

An automated algorithm for the detection of atrial fibrillat...

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Computers in Cardiology (CinC)

作者： Eric Helfenbein Richard Gregg James Lindauer Sophia Zhou Advanced Algorithm Research Center Philips Healthcare Thousand Oaks CA USA

Approximately 5% of diagnostic ECGs acquired in the hospital setting are from patients with pacemakers. A significant percentage of these patients are in atrial fibrillation or flutter (AF), and have increased risk of stroke. Many automated diagnostic algorithms abort analysis when paced rhythms are identified. The Philips DXL algorithm can detect AF in the presence of paced rhythms and provides interpretations for both rhythms. The algorithm uses QRST subtraction with frequency domain analysis of the residual. A decision tree classifier uses features from the power spectrum, as well as irregularity of non-paced beats. On a training database of 355 paced ECGs with 265 in AF, the algorithm had AF detection sensitivity of 76%, PPV of 82%, and specificity of 73%. On a testing set of 1,057 paced ECGs with 194 AF cases, the algorithm had sensitivity of 71%, PPV of 83%, and specificity of 97%. Automated detection of AF in the presence of pacing is a clinically valuable tool to assist cardiologists in ECG diagnosis, and can be done with relatively high accuracy.

关键词： Rhythm Electrocardiography Atrial fibrillation Classification algorithms algorithm design and analysis Lead Pacemakers

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Comparison of two automated methods for QT interval measurement

Comparison of two automated methods for QT interval measurem...

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Computers in Cardiology (CinC)

作者： R.E. Gregg S. Babaeizadeh D.Q. Feild E.D. Helfenbein J.M. Lindauer S.H. Zhou Advanced Algorithm Research Center Philips Medical Systems Andover MA USA

In this paper we compared two methods of automated QT interval measurement on standard ECG databases: the Root-Mean-Square (RMS) lead combining method aimed at QT monitoring and the method of median of lead-by-lead QT interval measurements. We used the PhysioNet PTB (N=548) and CSE measurement (N=125) standard databases. Both have reference QT interval measurements from a group of annotators. The last 10 seconds of each PTB record was downsampled from 1000 sample per second (sps) and an amplitude resolution of 1 muV to 500 sps and 5 muV in order to match the CSE set. PTB records #205 and #557 were excluded due to ventricular paced rhythm and artifact, respectively. Twenty five cases were excluded from the CSE set to match the selection of cases for IEC algorithm testing (IEC 60601-2-51). We processed all records using the Philips resting 12- lead ECG algorithm to generate representative beats for QT interval measurement. The RMS method measures QRS onset and end of Ton an RMS waveform constructed from 9 leads I, II, III and V1-V6. The lead-by-lead method takes the median QT interval across leads. The automated QT intervals by the RMS and lead-by-lead methods were compared to the reference manual QT measurements. The mean difference between the lead-by-lead QT and the reference QT was 1.7plusmn9.7 ms and 12.4plusmn23.0 ms (mean plusmnstandard deviation (SD)) for the CSE and PTB sets respectively. For the RMS method, the mean difference was -2.8plusmn11.1 ms and 10.3plusmn20.9 ms. F-tests indicate that the standard deviation between methods is not significantly different for the CSE set (P=0.18) or the PTB set (P=0.77). The lead-by-lead and RMS methods perform similarly, leading to the conclusion that the choice between them should be based on considerations such as the number of leads available or computational efficiency.

关键词： Heart rate interval Electrocardiography Drugs Computerized monitoring Bandwidth Measurement standards Databases Testing Patient monitoring Biomedical monitoring

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Synthesis of standard 12-lead electrocardiograms using two dimensional generative adversarial network

arXiv

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arXiv 2021年

作者： Zhang, Yu-He Babaeizadeh, Saeed Advanced Algorithm Research Center Philips Healthcare CambridgeMA United States

This paper proposes a two-dimensional (2D) bidirectional long short-term memory generative adversarial network (GAN) to produce synthetic standard 12-lead ECGs corresponding to four types of signals—left ventricular hypertrophy (LVH), left branch bundle block (LBBB), acute myocardial infarction (ACUTMI), and Normal. It uses a fully automatic end-to-end process to generate and verify the synthetic ECGs that does not require any visual inspection. The proposed model is able to produce synthetic standard 12-lead ECG signals with success rates of 98% for LVH, 93% for LBBB, 79% for ACUTMI, and 59% for Normal. Statistical evaluation of the data confirms that the synthetic ECGs are not biased towards or overfitted to the training ECGs, and span a wide range of morphological features. This study demonstrates that it is feasible to use a 2D GAN to produce standard 12-lead ECGs suitable to augment artificially a diverse database of real ECGs, thus providing a possible solution to the demand for extensive ECG datasets. © 2021, CC BY-NC-ND.

关键词： Generative adversarial networks

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Performance of a continuous real-time qt interval monitoring algorithm for the critical-care setting

Performance of a continuous real-time qt interval monitoring...

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Computers in Cardiology (CinC)

作者： E. D. Helfenbein S. H. Zhou D. Q. Feild J. M. Lindauer R. E. Gregg J. Y. Wang S. S. Kresge F. P. Michaud Philips Medical Systems Advanced Algorithm Research Center Milpitas CA USA

We developed an automated continuous real-time QTc interval monitoring algorithm for the critical-care setting. The performance of the QT interval measurement algorithm was tested on the PhysioNet adult QT ECG dataset (n=105), and on a pediatric ECG dataset (n=20) and a neonatal dataset (n=24) recorded from intensive care units. The algorithm performance is measured by sensitivity (the ability to measure the QT interval), and accuracy (the difference between the automated QT measurements and cardiologists' manual annotations). We obtained 92% sensitivity in the adult group, 85% in the pediatric group and 75% in the neonatal group. On the 95 adult cases which had both an algorithm and a cardiologist measurement, the mean difference was 1 ms with a standard deviation of 35 ms. On the pediatric ECGs, the mean difference was -12 ms with a standard deviation of 20 ms. In the neonatal cases, the mean difference was -6 ms with a standard deviation of 12 ms.

关键词： Heart rate interval Electrocardiography Pediatrics Cardiology Patient monitoring Real time systems Biomedical monitoring Computerized monitoring Databases Clustering algorithms

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Automatic detection of ECG lead-wire interchange for conventional and Mason-Likar lead systems

Automatic detection of ECG lead-wire interchange for convent...

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Computers in Cardiology (CinC)

作者： Chengzong Han Richard E Gregg Saeed Babaeizadeh Philips Healthcare Andover MA Advanced Algorithm Research Center Andover MA USA

Misconnection of ECG lead-wires can generate abnormal ECG and erroneous diagnosis. Existing methods for detecting lead-wire interchange were designed for ECG devices using conventional lead system. In this work we developed an automatic ECG cable interchange detection algorithm and compared the algorithm performance between conventional and Mason-Likar (ML) electrode placements. The algorithm was developed based on a decision tree classifier which uses beat morphology measurements that were obtained using Philips DXL ECG algorithm. The algorithm was evaluated for detecting limb cable interchanges on an independent database which included both conventional and ML ECG recordings for each subject (total 423 subjects). There was no statistically significant difference in terms of overall sensitivity and specificity. This morphology-based cable interchange detection algorithm showed similarly high performance for maintaining a low false positive rate for both lead systems. Therefore, in practice, the same algorithm may be used with either electrode placement without a need for a special configuration.

关键词： Electrocardiography Electrodes Lead Databases Abstracts Detection algorithms Myocardium

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An automated algorithm for the detection of atrial fibrillation in the presence of paced rhythms

An automated algorithm for the detection of atrial fibrillat...

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作者： Helfenbein, Eric Gregg, Richard Lindauer, James Zhou, Sophia Advanced Algorithm Research Center Philips Healthcare Thousand Oaks CA United States Philips Healthcare 3860 North First Street San Jose CA 95134 United States

ISBN: (纸本)9781424473182

关键词： Electrocardiograms

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