Electrocardiography

Combining Optical Character Recognition with Paper ECG Digitization

Author(s): Shambavi Ganesh, Pamela Bhatti, Mhmtjamil Alkhalaf, Shishir Gupta, Srini Tridandapani
Combining Optical Character Recognition with Paper ECG Digitization 698 514 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Objective: We propose a MATLAB-based tool to convert electrocardiography (ECG) waveforms from paper-based ECG records into digitized ECG signals that is vendor-agnostic. The tool is packaged as an open source…

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MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG

Author(s): Jing Zhang, Deng Liang, Aiping Liu, Min Gao, Xiang Chen, Xu Zhang, Xun Chenb
MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Automatic arrhythmia detection using 12-lead electrocardiogram (ECG) signal plays a critical role in early prevention and diagnosis of cardiovascular diseases. In the previous studies on automatic arrhythmia detection, most methods…

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Accurate Fiducial Point Detection Using Haar Wavelet for Beat-by-Beat Blood Pressure Estimation

Author(s): Muskan Singla, Syed Azeemuddin, Prasad Sistla
Accurate Fiducial Point Detection Using Haar Wavelet for Beat-by-Beat Blood Pressure Estimation 817 745 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Pulse Arrival Time (PAT) derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) for cuff-less Blood Pressure (BP) measurement has been a contemporary and widely accepted technique. However, the features extracted for…

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Near Real-Time Implementation of An Adaptive Seismocardiography — ECG Multimodal Framework for Cardiac Gating

Near Real-Time Implementation of An Adaptive Seismocardiography — ECG Multimodal Framework for Cardiac Gating

Author(s): Jingting Yao, Srini Tridandapani, Pamela Bhatti
Near Real-Time Implementation of An Adaptive Seismocardiography — ECG Multimodal Framework for Cardiac Gating 780 308 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

   Early Access Note: Early Access articles are new content made available in advance of the final electronic or print versions and result from IEEE’s Preprint or Rapid Post processes.…

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Deep Learning Based Proarrhythmia Analysis Using Field Potentials Recorded from Human Pluripotent Stem Cells Derived Cardiomyocytes

Deep Learning Based Proarrhythmia Analysis Using Field Potentials Recorded from Human Pluripotent Stem Cells Derived Cardiomyocytes

Author(s): Zeinab Golgooni, Sara Mirsadeghi, Mahdieh Soleymani Baghshah, Pedram Ataee, Hossein Baharvand, Sara Pahlavan, Hamid R. Rabiee
Deep Learning Based Proarrhythmia Analysis Using Field Potentials Recorded from Human Pluripotent Stem Cells Derived Cardiomyocytes 780 435 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

       Abstract: An early characterization of drug-induced cardiotoxicity may be possible by combining comprehensive in vitro proarrhythmia assay and deep learning techniques. We aimed to develop a method to automatically…

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An Open-Source Feature Extraction Tool for the Analysis of Peripheral Physiological Data

An Open-Source Feature Extraction Tool for the Analysis of Peripheral Physiological Data

Author(s): Mohsen Nabian, Yu Yin, Jolie Wormwood, Karen S. Quigley, Lisa F. Barrett, Sarah Ostadabba
An Open-Source Feature Extraction Tool for the Analysis of Peripheral Physiological Data 780 245 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

      Electrocardiogram, electrodermal activity, electromyogram, continuous blood pressure, and impedance cardiography are among the most commonly used peripheral physiological signals (biosignals) in psychological studies and healthcare applications, including health tracking,…

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An Adaptive Seismocardiography (SCG)-ECG Multimodal Framework

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

Author(s): Jingting Yao, Srini Tridandapani, William F. Auffermann, Carson A. Wick, Pamela Bhatti
An Adaptive Seismocardiography (SCG)-ECG Multimodal Framework for Cardiac Gating Using Artificial Neural Networks 780 377 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

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…

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Unobtrusive Detection of Simulated Orthostatic Hypotension and Supine Hy...

Unobtrusive Detection of Simulated Orthostatic Hypotension and Supine Hypertension using Ballistocardiogram and Electrocardiogram of Healthy Adults

Author(s): Isaac S. Chang, Narges Armanfard, Abdul Qadir Javaid, Jennifer Boger, Alex Mihailidis
Unobtrusive Detection of Simulated Orthostatic Hypotension and Supine Hypertension using Ballistocardiogram and Electrocardiogram of Healthy Adults 780 310 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Effective management of neurogenic orthostatic hypotension and supine hypertension (SH-OH) due autonomic failure requires a frequent and timely adjustment of medication throughout the day to maintain the blood pressure (BP)…

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Radial Pulse Spectrum Analysis as Risk Markers to Improve the Risk Stratification of Silent Myocardial Ischemia in Type 2 Diabetic Patients

Author(s): Chi-Wei Chang, Kuo-Meng Liao, Ying-Chun Chen, Sheng-Hung Wang, Ming-Yie Jan, Gin-Chung Wang
Radial Pulse Spectrum Analysis as Risk Markers to Improve the Risk Stratification of Silent Myocardial Ischemia in Type 2 Diabetic Patients 780 595 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

      Diabetic patients with silent myocardial ischemia (SMI) have elevated rates of morbidity and mortality and need intensive care and monitoring. An early predictor of SMI may lead to early…

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Detection of Cardiac Quiescence from B-Mode Echocardiography using a Correlation-Based Frame-to-Frame Deviation Measure

Detection of Cardiac Quiescence from B-Mode Echocardiography using a Correlation-Based Frame-to-Frame Deviation Measure 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Two novel methods for detecting cardiac quiescent phases from B-mode echocardiography using a correlation-based frame-to-frame deviation measure were developed. Accurate knowledge of cardiac quiescence is crucial to the performance of…

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