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).

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IEEE Journal of

Translational Engineering in Health and Medicine

2020
VOLUME 8
IJTEHM
8
The IEEE Journal of Translational Engineering in Health and Medicine Volume 8 was recently published.
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... Read more
A Decision Support System for Diabetes Chronic Care Models based on General Practitioner engagement and EHR data sharing
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... Read more
Articles
Quantification of Resting of Resting-state Ballistocardiogram Difference between Clinical and Non-clinical Populations for Ambient Monitoring of Heart Failure
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... Read more
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... Read more
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... Read more
Articles
LoCoMo-Net: A Low-Complex Deep Learning Framework for sEMG Based Hand Movement Recognition for Prosthetic Control
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)... Read more
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),... Read more
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),... Read more
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... Read more
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,... Read more
Articles
Performance Evaluation of Mixed Reality Display for Guidance During Transcatheter Cardiac Mapping and Ablation
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... Read more
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... Read more