IEEE Journal of
Translational Engineering in Health and Medicine
IEEE Journal of
Translational Engineering in Health and Medicine
IEEE Journal of Translational Engineering in Health and Medicine's unique aim is to publish original work in the intersection of engineering and clinical translation. The journal's focus is interdisciplinary collaborations between researchers, healthcare providers, and industry and aims to publish results and best practices from these translational efforts.
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Pamela Bhatti, PhD
Editor-in-chief
Editor-in-chief
Pamela Bhatti (S’05-M’06-SM'19) is an Associate Professor and Associate Chair for Innovation and Entrepreneurship at the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA. Her research is dedicated to overcoming sensory loss in human hearing through focused neural stimulation, and novel implantable sensors. Dr. Bhatti also conducts research in cardiac imaging to assess and monitor cardiovascular disease. She received her B.S. in Bioengineering from the University of California, Berkeley (1989), her M.S. in Electrical Engineering from the University of Washington (1993), and her Ph.D. in Electrical Engineering from the University of Michigan, Ann Arbor (2006). In 2013 she earned an M.S. in Clinical Research from Emory University and serves as the Georgia Tech Research, Education, and Career Development Director for the Atlanta Clinical and Translational Sciences Institute, an NIH-funded center. Committed to translating technology... Read more
Pamela Bhatti (S’05-M’06-SM'19) is an Associate Professor and Associate Chair for Innovation and Entrepreneurship at the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA. Her research is dedicated to overcoming sensory loss in human hearing through focused neural stimulation, and novel implantable sensors. Dr. Bhatti also conducts research in cardiac imaging to assess and monitor cardiovascular disease. She received her B.S. in Bioengineering from the University of California, Berkeley (1989), her M.S. in Electrical Engineering from the University of Washington (1993), and her Ph.D. in Electrical Engineering from the University of Michigan, Ann Arbor (2006). In 2013 she earned an M.S. in Clinical Research from Emory University and serves as the Georgia Tech Research, Education, and Career Development Director for the Atlanta Clinical and Translational Sciences Institute, an NIH-funded center. Committed to translating technology to the clinical setting, in 2016 she co-founded Camerad Technologies, a company dedicated to improving throughput and quality in radiology imaging.
Before completing her Ph.D. degree, she researched the detection of breast cancer with ultrasound imaging in the Department of Radiology, University of Michigan (1997-1999). Her industry experience includes embedded systems software development at Microware Corporation, Des Moines, IA, USA (1996-1997), local operating network applications development and customer support at Motorola Semiconductor, Austin, TX, USA (19941995), and research and fabrication of controlled-release drug delivery systems at Alza Corporation, Palo Alto, CA, USA (1986-1990).
Dr. Shangying Wang
JTEHM Top Reviewer 2020
JTEHM Top Reviewer 2020
Dr. Shangying Wang, a postdoctoral researcher at IBM Almaden Research Center, has been named the inaugural JTEHM Top Reviewer for her outstanding work during 2020. Thank you Dr. Wang for your dedication to JTEHM!
See the full list of reviewers below.
Dr. Shangying Wang, a postdoctoral researcher at IBM Almaden Research Center, has been named the inaugural JTEHM Top Reviewer for her outstanding work during 2020. Thank you Dr. Wang for your dedication to JTEHM!
See the full list of reviewers below.
Updates
IEEE Journal of
Translational Engineering in Health and Medicine
2020
VOLUME 9
IJTEHM
VOLUME 9
IJTEHM
9
The IEEE Journal of Translational Engineering in Health and Medicine Volume 9 was recently published.
Combining Optical Character Recognition with Paper ECG Digitization
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 standalone graphical user interface (GUI) based application. Methods and procedures:...
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Posted on 3 JUN 2021
Automated Diagnosis of COVID-19 using Deep Features and Parameter Free BAT Optimization
Background: Timely and precise identification of COVID-19 is an arduous task owing to the scarcity and inefficiency of the medical test kits. This has resulted in medical professionals turning towards Computed Tomography (CT) scans. Efforts are being made to design...
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Posted on 10 MAY 2021
Recent News
JTEHM Reviewers and Exceptional Reviewers (Updated June 2020)
The JTEHM editorial board acknowledges the contributions of all reviewers in our annual reviewer list. In the past, the board has named a few reviewers as “Exceptional Reviewers.” Beginning with the list of 2020 reviewers the board has decided to...
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Posted on 2 JUN 2021
Articles
Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI
Objective: To introduce an MRI in-plane resolution enhancement method that estimates High-Resolution (HR) MRIs from Low-Resolution (LR) MRIs. Method & Materials: Previous CNN-based MRI super-resolution methods cause loss of input image information due to the pooling layer. An Autoencoder-inspired Convolutional...
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Posted on 3 MAY 2021
Articles
Detecting Cataract Using Smartphones
Objective: Cataract, which is the clouding of the crystalline lens, is the most prevalent eye disease accounting for 51% of all eye diseases in the U.S. Cataract is a progressive disease, and its early detection is critical for preventing blindness....
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Posted on 22 APR 2021
Articles
Clinically applicable machine learning approaches to identify attributes of Chronic Kidney Disease (CKD) for use in low-cost diagnostic screening
Objective: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis...
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Posted on 16 APR 2021
Articles
Identifying hand use and hand roles after stroke using egocentric video
Objective: Upper limb (UL) impairment impacts quality of life, but is common after stroke. UL function evaluated in the clinic may not reflect use in activities of daily living (ADLs) after stroke, and current approaches for assessment at home rely...
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Posted on 9 APR 2021
Articles
Development of a Smart Hallway for Markerless Human Foot Tracking and Stride Analysis
Objective: In this research, a marker-less ‘smart hallway’ is proposed where stride parameters are computed as a person walks through an institutional hallway. Stride analysis is a viable tool for identifying mobility changes, classifying abnormal gait, estimating fall risk, monitoring...
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Posted on 30 MAR 2021
Articles
Detecting effect of levodopa in Parkinson’s disease patients using sustained phonemes
Background: Parkinson’s disease (PD) is a multi-symptom neurodegenerative disease generally managed with medications, of which levodopa is the most effective. Determining the dosage of levodopa requires regular meetings where motor function can be observed. Speech impairment is an early symptom...
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Posted on 18 MAR 2021
Articles
MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG
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 concatenated 12 leads of ECG into a matrix, and then...
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Posted on 10 MAR 2021
Articles
Stomach 3D Reconstruction Using Virtual Chromoendoscopic Images
Objective. Gastric endoscopy is a golden standard in the clinical process that enables medical practitioners to diagnose various lesions inside a patient’s stomach. If a lesion is found, a success in identifying the location of the found lesion relative to...
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Posted on 1 MAR 2021
Articles
MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG
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 concatenated 12 leads of ECG into a matrix, and then...
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Posted on 10 MAR 2021
Articles
Intraductal Tissue Sampling Device Designed for the Biliary Tract
Clinical sampling of tissue that is read by a pathologist is currently the gold standard for making a disease diagnosis, but the few minimally invasive techniques available for small duct biopsies have low sensitivity, increasing the likelihood of false negative...
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Posted on 5 FEB 2021
Articles
Massage Therapy’s Effectiveness on the decoding EEG rhythms of Left/Right Motor Imagery and Motion Execution in Patients with Skeletal Muscle Pain
Objective: Most of effectiveness assessments of the widely-used Massage therapy were based on subjective routine clinical assessment tools, such as Visual Analogue Scale (VAS) score. However, few studies demonstrated the impact of massage on the Electroencephalograph (EEG) rhythm decoding of...
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Posted on 4 FEB 2021
Articles
Autonomous Robot for Removing Superficial Traumatic Blood
Baiquan Su, Yu Shi, Xintong Li, Yi Gong, Han Li, Zifeng Ren, Yijing Xia, He Wang, Yucheng Zhang, Wei Yao, Junchen Wang, Jie Tang
Objective: To remove blood from an incision and find the incision spot is a key task during surgery, or else over discharge of blood will endanger a patient’s life. However, the repetitive manual blood removal involves plenty of workload contributing...
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Posted on 3 FEB 2021
Articles
Design, Simulation, and Development of a BioSensor for Viruses Detection using FPGA
Abstract:Objective: Impedance based biosensing provides a unique, highly sensitive electrical approach to biomolecule detection, cell growth, and other biological events. To date, an impedance change due to the cell growth has been considered as a solution to detect some changes...
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Posted on 2 FEB 2021
Articles, Uncategorized
mHealth Technology Translation in a Limited Resources Community – Process, Challenges, and Lessons Learned from a Limited Resources Community of Chiang Mai Province, Thailand
Waraporn Boonchieng, Jintana Chaiwan, Bijaya Shrestha, Manash Shrestha, Adam J.O. Dede, Ekkarat Boonchieng
Objective: This report aims to provide practical advice about the implementation of a public health monitoring system using both geographic information system technology and mobile health, a term used for healthcare delivery via mobile devices. application amongst household residents and...
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Posted on 28 JAN 2021
Articles
Hand-held zoom micro-imaging system based on microfluidic chip for point-of-care testing (POCT) of vaginal inflammation
Background: Vaginitis is a common and very private disease, and the current diagnosis is a frequent go to the hospital for testing. Objective: In order to improve the convenience and speed of detection, in this paper, we have developed a...
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Posted on 27 JAN 2021
Articles
Pathologic blood samples tolerate exposure to vibration and high turbulence in simulated drone flights, but plasma samples should be centrifuged after flight.
Karl Arne Johannessen, Nina Kristin Steen Wear, Karin Toska, Morten Hansbø, Jens Petter Berg, Erik Fosse
Abstract: Most of the previous studies of drone transport of blood samples examined normal blood samples transported under tranquil air conditions. We studied the effects of 1- and 2-hour drone flights using random vibration and turbulence simulation (10-30 g-force) on...
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Posted on 23 JAN 2021
Articles
A deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data
Md. Rashed-Al-Mahfuz, Mohammad Ali Moni, Shahadat Uddin, Salem A. Alyami, Mattew A. Summers, Valsamma Eapen
Background: Diagnosing epileptic seizures using electroencephalogram (EEG) in combination with deep learning computational methods has received much attention in recent years. However, to date, deep learning techniques in seizure detection have not been effectively harnessed due to sub-optimal classifier design...
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Posted on 13 JAN 2021
Articles
Registration Techniques for Clinical Applications of Three-Dimensional Augmented Reality Devices
Christopher M. Andrews, Alexander B. Henry, Ignacio M. Soriano, Michael K. Southworth, Jonathan R. Silva
Many clinical procedures would benefit from direct and intuitive real-time visualization of anatomy, surgical plans, or other information crucial to the procedure. Three-dimensional augmented reality (3D-AR) is an emerging technology that has the potential to assist physicians with spatial reasoning...
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Posted on 30 DEC 2020
Articles
Quantifying Pathological Synergies in the Upper Extremity of Stroke Subjects With the Use of Inertial Measurement Units: A pilot Study
Miguel M. C. Bhagubai, Gerjan Wolterink, Anne Schwarz, Jeremia P.O. Held, Bert-Jan F. van Beijnum, Peter H. Veltink
Abstract Background: Stroke is one of the main causes of disability in the world, causing loss of motor function on mainly one side of the body. A proper assessment of motor function is required to help to direct and evaluate...
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Posted on 8 DEC 2020
Articles
Assessment of residual radioactivity by a comprehensive wireless, wearable device in thyroid cancer patients undergoing radionuclide therapy and comparison with the results of a home device: a feasibility study
R. Gallachio, D. Scapicchio, A. Nardelli, T. Pellegrino, M. Prisco, P. Mainenti, C. Sirignano, P. Pedicini, G. Storto
Objective: To investigate the feasibility of using a wireless wearable device (WD) in differentiated thyroid cancer (DTC) patients undergoing radionuclide therapy with I-131 (RAI) and protected hospitalization, this study compared the measurements of residual radioactivity obtained with those registered by...
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Posted on 3 DEC 2020
Articles
Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients using Primary Care Electronic Health Records
A growing elderly population suffering from incurable, chronic conditions such as dementia present a continual strain on medical services due to mental impairment paired with high comorbidity resulting in increased hospitalization risk. The identification of at risk individuals allows for...
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Posted on 25 NOV 2020
Articles
Novel Technique for Noninvasive Detection of Localized Dynamic Brain Signals by Using Transcranial Static Magnetic Fields
The techniques for noninvasive measurement of brain function such as electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS) have been used in diagnosing brain conditions. However, the conventional techniques have critical limitations of spatial...
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Posted on 18 NOV 2020
Articles
Design of a Device for Lower Limb Prophylaxis and Exercise
The problem of immobility of legs leading to a potentially life threatening condition including deep venous thrombosis (DVT) is well known. The reduced mobility of leg affects a large number of patients in a wide range of clinical scenarios spanning...
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Posted on 10 NOV 2020
Articles
Quantifying Tremor in Essential Tremor using Inertial Sensors — Validation of an Algorithm
Background Assessment of essential tremor is often done by a trained clinician who observes the limbs during different postures and actions and subsequently rates the tremor. While this method has been shown to be reliable, the inter- and intra-rater reliability...
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Posted on 22 OCT 2020
Articles
A Decision Support System for Diabetes Chronic Care Models based on General Practitioner engagement and EHR data sharing
Emanuele Frontoni, Luca Romeo, Michele Bernardini, Sara Moccia, Lucia Migliorelli, Marina Paolanti, Alessandro Ferri, Paolo Misericordia, Adriano Mancini, Primo Zingaretti
Objective Decision support systems (DSS) have been developed and promoted for their potential to improve quality of health care. However, there is a lack of common clinical strategy and a poor management of clinical resources and erroneous implementation of preventive...
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Posted on 14 OCT 2020
Articles
Quantification of Resting of Resting-state Ballistocardiogram Difference between Clinical and Non-clinical Populations for Ambient Monitoring of Heart Failure
Isaac S. Chang, Susanna Mak, Narges Armanfard, Jennifer Boger, Sherry L. Grace, Amaya Arcelus, Caroline Chessex, Alex Mihailidis
A ballistocardiogram (BCG) is a versatile bio-signal that enables ambient remote monitoring of heart failure (HF) patients in a home setting, achieved through embedded sensors in the surrounding environment. Numerous methods of analysis are available for extracting physiological information using...
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Posted on 12 OCT 2020
Articles
Side-Channel Sensing: Exploiting Side-Channels to Extract Information for Medical Diagnostics and Monitoring
Abstract Information within systems can be extracted through side-channels; unintended communication channels that leak information. The concept of side-channel sensing is explored, in which sensor data is analysed in non-trivial ways to recover subtle, hidden or unexpected information. Practical examples...
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Posted on 7 OCT 2020
Articles
Early detection of Acute Chest Syndrome through electronic recording and analysis of auscultatory percussion
Acute chest syndrome (ACS) is the leading cause of death among people with sickle cell disease. ACS is clinically defined and diagnosed by the presence of a new pulmonary infiltrate on chest imaging with accompanying fever and respiratory symptoms like...
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Posted on 6 OCT 2020
Articles
LoCoMo-Net: A Low-Complex Deep Learning Framework for sEMG Based Hand Movement Recognition for Prosthetic Control
Arvind Gautam, Madhuri Panwar, Archana Wankhede, Sridhar Arjunan, Ganesh Naik, Amit Charyya, Dinesh Kumar
Background: The enhancement in the performance of the myoelectric pattern recognition techniques based on deep learning algorithm possess computationally expensive and exhibit extensive memory behavior. Therefore, in this paper we report a deep learning framework named ‘Low-Complex Movement recognition-Net’ (LoCoMo-Net)...
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Posted on 17 SEP 2020
Articles
Evaluation of the Vibe actigraph in patients with chronic obstructive pulmonary disease: A pilot study
Study objective: To validate the Vibe actigraph in assessing sleep-wake patterns compared to polysomnography (PSG) in patients with COPD. Methods: Nine stable COPD patients wore actigraphs while undergoing PSG. The correlation between total sleep time (TST), total sleep period (TSP),...
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Posted on 26 AUG 2020
Articles
Evaluation of the Vibe actigraph in patients with chronic obstructive pulmonary disease: A pilot study
Study objective: To validate the Vibe actigraph in assessing sleep-wake patterns compared to polysomnography (PSG) in patients with COPD. Methods: Nine stable COPD patients wore actigraphs while undergoing PSG. The correlation between total sleep time (TST), total sleep period (TSP),...
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Posted on 26 AUG 2020
Articles
Effect of laryngeal mask airway insertion on parameters derived from catacrotic phase of photoplethysmography under different concentrations of remifentanil
Background: Some parameters have been extracted from photoplethysmography (PPG) with a good relativity with nociception, but without encouraging results in qualifying the balance of nociception-anti-nociception (NAN). The features of PPG have not been thoroughly depicted and more prospective univariate parameters...
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Posted on 18 AUG 2020
Articles
Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos
Objective: Novel applications of transcranial Doppler (TCD) ultrasonography, such as the assessment of cerebral vessel narrowing/occlusion or the non-invasive estimation of intracranial pressure (ICP), require high-quality maximal flow velocity waveforms. However, due to the low signal-to-noise ratio of TCD spectrograms,...
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Posted on 14 AUG 2020
Articles
Performance Evaluation of Mixed Reality Display for Guidance During Transcatheter Cardiac Mapping and Ablation
Michael K. Southworth, Jennifer N. Avari Silva, Walter M. Blume, George F. Van Hare, Aarti S. Dalal, Jonathan R. Silva
Cardiac electrophysiology procedures present the physician with a wealth of 3D information, typically presented on fixed 2D monitors. New developments in wearable mixed reality displays offer the potential to simplify and enhance 3D visualization while providing hands-free, dynamic control of...
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Posted on 14 AUG 2020
Articles
Wearable Device-Independent Next Day Activity and Next Night Sleep Prediction for Rehabilitation Populations
Wearable sensor-based devices are increasingly applied in free-living and clinical settings to collect fine-grained, objective data about activity and sleep behavior. The manufacturers of these devices provide proprietary software that labels the sensor data at specified time intervals with activity...
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Posted on 14 AUG 2020