Electrocardiography

A Wavelet-Based Approach for Motion Artifact Reduction in Ambulatory Seismocardiography
A Wavelet-Based Approach for Motion Artifact Reduction in Ambulatory Seismocardiography 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
Wearable sensing has become a vital approach to cardiac health monitoring, and seismocardiography (SCG) is emerging as a promising technology in this field. However, the applicability of SCG is hindered… read more

Identification of Coronary Culprit Lesion in ST Elevation Myocardial Infarction by Using Deep Learning
Identification of Coronary Culprit Lesion in ST Elevation Myocardial Infarction by Using Deep Learning 1884 2560 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
Objective: Early revascularization of the occluded coronary artery in patients with ST elevation myocardial infarction (STEMI) has been demonstrated to decrease mortality and morbidity. Currently, physicians rely on features of… read more

Impaired brain-heart relation in patients with methamphetamine use disorder during VR induction of drug cue reactivity
Impaired brain-heart relation in patients with methamphetamine use disorder during VR induction of drug cue reactivity 1978 2560 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
Objective: Methamphetamine use disorder (MUD) is an illness associated with severe health consequences. Virtual reality (VR) is used to induce the drug-cue reactivity and significant EEG and ECG abnormalities were… read more

Combining Optical Character Recognition with Paper ECG Digitization
Author(s)3: 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)3: 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)3: 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)3: 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)3: 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)3: 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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