Mohamed (Moe) Elgendi (0000-0003-1831-0202)

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Mohamed (Moe) Elgendi is an Assistant Professor at Khalifa University with extensive experience in Biomedical Engineering, focusing on AI-driven innovations for health. His expertise spans wearable technologies, contact and non-contact biomedical sensing, textiles, machine learning, algorithm development, data analysis, health data visualization, and knowledge translation. He has also received specialized training in data analytics from MIT.

Previously, Dr. Elgendi served as the Deputy Director of the Biomedical and Mobile Health Technology Lab at ETH Zurich, where he played a key role in establishing the lab, mentoring students, and developing course materials. He has also held positions at Nanyang Technological University, the University of Alberta, and the University of British Columbia.

Dr. Elgendi was ranked among the top 2% of scientists worldwide by Stanford University in 2021, 2022, and 2023. He serves on the editorial boards of several journals and has published over 170 scientific works. He has secured numerous competitive grants and contributed to global health initiatives. In addition to his research, Dr. Elgendi has supervised over 40 MSc and BSc thesis students, many of whom have gone on to secure PhD scholarships at prestigious institutions such as MIT and Harvard.

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Khalifa University of Science and Technology: Abu Dhabi, AE

2024-08-12 to present | A/Professor (Biomedical Engineering and Biotechnology)

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Mohamed (Moe) Elgendi

https://orcid.org/0000-0003-1831-0202

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Employment (3)

Khalifa University of Science and Technology: Abu Dhabi, AE

ETH Zurich: Zurich, CH

BC Children's Hospital: Vancouver, BC, CA

Education and qualifications (1)

Charles Darwin University: Casuarina, NT, AU

Works (50 of 104)

Vital signs-based healthcare kiosks for screening chronic and infectious diseases: a systematic review

Variability and repeatability of spinal manipulation force–time characteristics in thoracic spinal manipulation on a manikin

Photoplethysmography Features Correlated with Blood Pressure Changes

Recommendations for evaluating photoplethysmography-based algorithms for blood pressure assessment

A machine learning-based approach for constructing remote photoplethysmogram signals from video cameras

Users' Acceptability and Perceived Efficacy of mHealth for Opioid Use Disorder: Scoping Review

Evaluating reliability in wearable devices for sleep staging

Innovative Approaches to Menstruation and Fertility Tracking Using Wearable Reproductive Health Technology: Systematic Review

Optimizing wearable motion tracking by assessing sagittal joint angle accuracy with minimal sensor use

An Open-Source Graphical User Interface-Embedded Automated Electrocardiogram Quality Assessment: A Balanced Class Representation Approach

Opportunities and challenges for sweat-based monitoring of metabolic syndrome via wearable technologies

Users' Acceptability and Perceived Efficacy of mHealth for Opioid Use Disorder: Scoping Review (Preprint)

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review

Conversational Agents and Avatars for Cardiometabolic Risk Factors and Lifestyle-Related Behaviors: Scoping Review

PPG2ECGps: An End-to-End Subject-Specific Deep Neural Network Model for Electrocardiogram Reconstruction from Photoplethysmography Signals without Pulse Arrival Time Adjustments

Prevalence, causes, and impact of non-visualized pregnancy losses in a recurrent pregnancy loss population

GRGB rPPG: An Efficient Low-Complexity Remote Photoplethysmography-Based Algorithm for Heart Rate Estimation

Innovative Approaches to Menstruation and Fertility Tracking Using Wearable Reproductive Health Technology: Systematic Review (Preprint)

Heart and Breathing Rate Variations as Biomarkers for Anxiety Detection

The Use of Audio Signals for Detecting COVID-19: A Systematic Review

Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis

Dataset of Psychological Scales and Physiological Signals Collected for Anxiety Assessment Using a Portable Device

Clinical use of artificial intelligence in endometriosis: a scoping review

Blood pressure measurement using only a smartphone

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review (Preprint)

Ethnic disparities in publicly-available pulse oximetry databases

Conversational Agents and Avatars for Cardiometabolic Risk Factors and Lifestyle-Related Behaviors: Scoping Review (Preprint)

Photoplethysmography (PPG): state-of-the-art methods and applications

Classification of blood pressure in critically ill patients using photoplethysmography and machine learning

Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

Machine Learning Ranks ECG as an Optimal Wearable Biosignal for Assessing Driving Stress

The Evaluation of Deep Neural Networks and X-Ray as a Practical Alternative for Diagnosis and Management of COVID-19

Multimodal Photoplethysmography-Based Approaches for Improved Detection of Hypertension

Cuffless Single-Site Photoplethysmography for Blood Pressure Monitoring

Characteristics of a Highly Cited Article: A Machine Learning Perspective

The use of photoplethysmography for assessing hypertension

How Effective Is Pulse Arrival Time for Evaluating Blood Pressure? Challenges and Recommendations from a Study Using the MIMIC Database

Assessing Anxiety Disorders Using Wearable Devices: Challenges and Future Directions

Active right atrial emptying fraction predicts reduced survival and increased adverse events in childhood pulmonary arterial hypertension

High performance EEG feature extraction for fast epileptic seizure detection

Hypertension Assessment Using Photoplethysmography: A Risk Stratification Approach

Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification

Can Photoplethysmography Replace Arterial Blood Pressure in the Assessment of Blood Pressure?

Hypertension Assessment via ECG and PPG Signals: An Evaluation Using MIMIC Database

Robust detection of epileptic seizures based on L1-penalized robust regression of EEG signals

Subliminal Priming—State of the Art and Future Perspectives

An optimal filter for short photoplethysmogram signals

The Voice of the Heart: Vowel-Like Sound in Pulmonary Artery Hypertension

Toward Generating More Diagnostic Features from Photoplethysmogram Waveforms

A new, short-recorded photoplethysmogram dataset for blood pressure monitoring in China

Peer review (1 review for 1 publication/grant)