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1. Full Text Deep learning approach for active classification of electrocardiogram signals
by Rahhal, M.M. Al and Bazi, Yakoub and AlHichri, Haikel and Alajlan, Naif and Melgani, Farid and Yager, R.R
Information sciences, ISSN 0020-0255, 06/2016, Volume 345, pp. 340 - 354
ECG signal classification | Feature learning | Denoising autoencoder (DAE) | Active learning (AL) | Deep neural network (DNN) | Computer Science, Information Systems | Technology | Computer Science | Science & Technology | Electrocardiography | Rankings | Arrhythmia | Neural networks | Analysis | Electrocardiogram | Learning | Recommendations | Databases | Classification | Entropy | Representations | Retraining
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2. Full Text Graphene-clad textile electrodes for electrocardiogram monitoring
by Yapici, Murat Kaya and Alkhidir, Tamador and Samad, Yarjan Abdul and Liao, Kin
Sensors and actuators. B, Chemical, ISSN 0925-4005, 12/2015, Volume 221, pp. 1469 - 1474
Textile | Flexible | Electrode | Graphene | Electrocardiogram | Biosensor | ECG | Wearable | Physical Sciences | Chemistry | Technology | Instruments & Instrumentation | Electrochemistry | Chemistry, Analytical | Science & Technology | Electrodes | Electrocardiography | Graphite | Aerospace engineering | Silver | Textile composites | Echocardiography | Fabrics | Monitoring | Textiles
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3. Full Text Occult atrial fibrillation in cryptogenic stroke: Detection by 7-day electrocardiogram versus implantable cardiac monitors
by Ritter, Martin A and Kochhäuser, Simon and Duning, Thomas and Reinke, Florian and Pott, Christian and Dechering, Dirk G and Eckardt, Lars and Ringelstein, E. Bernd
Stroke (1970), ISSN 0039-2499, 05/2013, Volume 44, Issue 5, pp. 1449 - 1452
7-day Holter ECG | intermittent atrial fibrillation | stroke | implantable cardiac monitor | Clinical Neurology | Peripheral Vascular Disease | Neurosciences & Neurology | Life Sciences & Biomedicine | Cardiovascular System & Cardiology | Science & Technology | Cardiology. Vascular system | Heart | Neurology | Cardiac dysrhythmias | Biological and medical sciences | Vascular diseases and vascular malformations of the nervous system | Medical sciences | Outpatients | Electrocardiography, Ambulatory - instrumentation | Humans | Middle Aged | Atrial Fibrillation - complications | Electrocardiography - instrumentation | Stroke - complications | Female | Male | Aged | Atrial Fibrillation - diagnosis | Index Medicus
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4. Full Text Quiz: Electrocardiogram
by Sorokivskyy, Mykhaylo
Heart vessels and transplantation, ISSN 1694-7886, 06/2018, Volume 2, Issue Issue 2, p. 65
quiz | ECG
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5. Full Text An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks
by Poungponsri, Suranai and Yu, Xiao-Hua
Neurocomputing (Amsterdam), ISSN 0925-2312, 10/2013, Volume 117, pp. 206 - 213
ECG signal noise reduction | Neural networks | Wavelet transform | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Applied sciences | Connectionism. Neural networks | Artificial intelligence | Exact sciences and technology | Computer science; control theory; systems | Electrical engineering | Computer-generated environments | Computer simulation | Electrocardiogram | Electrocardiography | Heart diseases | Noise control | Electrodes | Noise | Adaptive filters | Muscles | Spectra | Contamination
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6. Full Text Low-dose computed tomography coronary angiography with prospective electrocardiogram triggering: Feasibility in a large population
by Buechel, Ronny R and Husmann, Lars and Herzog, Bernhard A and Pazhenkottil, Aju P and Nkoulou, Rene and Ghadri, Jelena R and Treyer, Valerie and Von Schulthess, Patrick and Kaufmann, Philipp A
Journal of the American College of Cardiology, ISSN 0735-1097, 01/2011, Volume 57, Issue 3, pp. 332 - 336
feasibility | prospective ECG triggering | low radiation dose | CT coronary angiography | Cardiac & Cardiovascular Systems | Life Sciences & Biomedicine | Cardiovascular System & Cardiology | Science & Technology | Cardiology. Vascular system | Heart | Cardiovascular system | Radiodiagnosis. Nmr imagery. Nmr spectrometry | Investigative techniques, diagnostic techniques (general aspects) | Biological and medical sciences | Medical sciences | Coronary heart disease | Prospective Studies | Humans | Middle Aged | Tomography, X-Ray Computed - methods | Male | Feasibility Studies | Young Adult | Coronary Artery Disease - diagnostic imaging | Coronary Angiography - methods | Coronary Artery Disease - physiopathology | Coronary Artery Disease - diagnosis | Adolescent | Aged, 80 and over | Adult | Female | Aged | Electrocardiography - methods | Population Surveillance - methods | Heart rate | Body mass index | Medical imaging | Scanners | Electrocardiography | Cardiovascular disease | Angina pectoris | Index Medicus | Abridged Index Medicus
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7. Full Text Human identification with electrocardiogram
by Tseng, Kuo-Kun and Fu, Lean and Liu, Linlin and Lee, Dachao and Wang, Chao and Li, Lingao and Meng, Yao
Enterprise information systems, ISSN 1751-7575, 08/2018, Volume 12, Issue 7, pp. 798 - 819
wearable device | human identification | ECG Recognition | human verification | ECG sensor | Computer Science, Information Systems | Technology | Computer Science | Science & Technology
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8. Full Text A review of electrocardiogram filtering
by Luo, Shen, PhD and Johnston, Paul
Journal of electrocardiology, ISSN 0022-0736, 2010, Volume 43, Issue 6, pp. 486 - 496
Cardiovascular | Frequency domain | Aliasing | ECG filter | Linear phase | Ringing artifact | Magnitude distortion | ECG standards | Signal Processing, Computer-Assisted | Artifacts | Algorithms | Electrocardiography - methods | Diagnosis, Computer-Assisted - methods | Electrocardiography | Analysis | Electrocardiogram | Index Medicus
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9. Full Text Diagnostic Accuracy of Coronary Computed Tomography Angiography. A Comparison Between Prospective and Retrospective Electrocardiogram Triggering
by Pontone, Gianluca and Andreini, Daniele and Bartorelli, Antonio L and Cortinovis, Sarah and Mushtaq, Saima and Bertella, Erika and Annoni, Andrea and Formenti, Alberto and Nobili, Enrica and Trabattoni, Daniela and Montorsi, Piero and Ballerini, Giovanni and Agostoni, Piergiuseppe and Pepi, Mauro
Journal of the American College of Cardiology, ISSN 0735-1097, 07/2009, Volume 54, Issue 4, pp. 346 - 355
accuracy | prospective ECG triggering | low dose | multidetector computed tomography | evaluability | Cardiac & Cardiovascular Systems | Life Sciences & Biomedicine | Cardiovascular System & Cardiology | Science & Technology | Cardiology. Vascular system | Cardiovascular system | Radiodiagnosis. Nmr imagery. Nmr spectrometry | Biological and medical sciences | Investigative techniques, diagnostic techniques (general aspects) | Medical sciences | Coronary Angiography - methods | Coronary Artery Disease - diagnosis | Humans | Middle Aged | Sensitivity and Specificity | Electrocardiography | Female | Male | Tomography, X-Ray Computed | Aged | Radiation Dosage | Heart | Confidence intervals | Heart rate | Accuracy | Medical imaging | Coronary vessels | Work stations | Tomography | Cardiovascular disease | Software | Patients | Index Medicus | Abridged Index Medicus
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10. Full Text PEA: Parallel electrocardiogram-based authentication for smart healthcare systems
by Zhang, Yin and Gravina, Raffaele and Lu, Huimin and Villari, Massimo and Fortino, Giancarlo
Journal of network and computer applications, ISSN 1084-8045, 09/2018, Volume 117, pp. 10 - 16
ECG | Parallel processing | Healthcare system | Biometric | Authentication | Computer Science, Interdisciplinary Applications | Computer Science, Hardware & Architecture | Computer Science, Software Engineering | Technology | Computer Science | Science & Technology
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11. Full Text Generating electrocardiogram signals by deep learning
by Wulan, Naren and Wang, Wei and Sun, Pengzhong and Wang, Kuanquan and Xia, Yong and Zhang, Henggui
Neurocomputing (Amsterdam), ISSN 0925-2312, 09/2020, Volume 404, pp. 122 - 136
Deep learning | Evaluation approach | Short-term Fourier transform | μ-Law companding transformation | Stationary wavelet transform | Synthetic ECG | Generative model | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Computer science | Algorithms | Neural networks | Analysis | Electrocardiogram | Electrocardiography | Signal processing | Models
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12. Full Text Normal values of the electrocardiogram for ages 16–90 years
by Rijnbeek, Peter R., PhD and van Herpen, Gerard, MD, PhD and Bots, Michiel L., MD, PhD and Man, Sumche, MD and Verweij, Niek, MD and Hofman, Albert, MD, PhD and Hillege, Hans, MD, PhD and Numans, Matthijs E., MD, PhD and Swenne, Cees A., PhD and Witteman, Jacqueline C.M., PhD and Kors, Jan A., PhD
Journal of electrocardiology, ISSN 0022-0736, 2014, Volume 47, Issue 6, pp. 914 - 921
Cardiovascular | POPULATION | SEX | ECG | WAVE | Normal values | Electrocardiogram | LEADS | Adult | Normal limits | HEART-RATE | AMPLITUDES | Elderly | VECTORCARDIOGRAM | Cardiac & Cardiovascular Systems | Life Sciences & Biomedicine | Cardiovascular System & Cardiology | Science & Technology | Diagnosis, Computer-Assisted - standards | Reproducibility of Results | Models, Cardiovascular | Humans | Middle Aged | Netherlands - epidemiology | Electrocardiography - standards | Male | Reference Values | Sex Characteristics | Young Adult | Aging - physiology | Computer Simulation | Sensitivity and Specificity | Adolescent | Diagnosis, Computer-Assisted - methods | Aged, 80 and over | Heart Rate - physiology | Female | Aged | Electrocardiography - methods | Index Medicus
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13. Full Text A novel method for detecting R-peaks in electrocardiogram (ECG) signal
by Manikandan, M.Sabarimalai and Soman, K.P
Biomedical signal processing and control, ISSN 1746-8094, 03/2012, Volume 7, Issue 2, pp. 118 - 128
QRS detection | Biosignal processing | ECG analysis | Signal detection | Engineering | Technology | Engineering, Biomedical | Science & Technology | Electrocardiography | Arrhythmia | Electrocardiogram | Analysis | Methods | Detectors
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