214 citations · 442 across the 48 of their papers we have counts for
49 papers
Circadian Derived Features for Early Discrimination Across Insomnia Severity Levels: At Least 8 Weeks of Monitoring Are Needed for Clinically Meaningful Assessment
Soheil Saghafi, Thomas C. Neylan, Qiao Li +2
Background: Wearable devices provide continuous, objective measures of daily activity and offer promise for assessing sleep disorders. However, the minimum monitoring duration need…
TAMI: Temporally Aligned, Missingness-Aware, and Interpretable Multimodal Fusion for Mental Health Assessment in Older Adults with Mild Cognitive Impairment
Merna Bibars, Bolaji Omofojoye, Allan I. Levey +3
Depression and anxiety in older adults with Mild Cognitive Impairment (MCI) are frequently underdiagnosed due to limited access to care. Multimodal analysis of remote clinical inte…
Cross-Modal Generative Framework for Signal Translation from Fetal-Maternal Electrocardiograms to Fetal Doppler Waveforms
Tongli Su, Alireza Rafiei, Marly van Assen +4
Fetal electrocardiogram (fECG) and Doppler ultrasound provide complementary views of fetal cardiovascular function: fECG captures electrical activity while Doppler reflects mechani…
SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models
Feng Wu, Harsh Deep, Eric Lehman +5
Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, multichannel signal complexity, inherent…
Prediction of Challenging Behaviors Associated with Profound Autism in a Classroom Setting Using Wearable Sensors
Yadhu Kartha, Conor Anderson, Jenny Foster +6
Autism Spectrum Disorder (ASD) is characterized by challenges with social interaction and communication and by restricted or repetitive patterns of thought and behavior, with signi…
Multi-View Hierarchical Representation Learning of Fetal Hemodynamics for Maternal Hypertension Detection at the Edge
Alireza Rafiei, Anahí Venzor Strader, Esteban Castro Aragón +6
Hypertensive disorders of pregnancy remain a leading cause of maternal and fetal morbidity worldwide, yet diagnosis relies on intermittent cuff-based blood pressure measurements th…
An Open-Source, Open Data Approach to Activity Classification from Triaxial Accelerometry in an Ambulatory Setting
Sepideh Nikookar, Edward Tian, Harrison Hoffman +7
The accelerometer has become an almost ubiquitous device, providing enormous opportunities in healthcare monitoring beyond step counting or other average energy estimates in 15-60…
Modeling Metabolic State Transitions in Obesity Using a Time-Varying Lambda-Omega Framework
Soheil Saghafi, Gari D. Clifford
Obesity does not emerge abruptly; rather, it develops gradually over extended periods. The gradual progression often prevents early recognition of physiological changes until exces…
From PhysioNet to Foundation Models -- A History and Potential Futures
Gari D. Clifford
Over the last 35 years, the sharing of medical data and models for research has evolved from sneakernet to the internet - from mailing magnetic tapes and compact discs of a handful…
CARE-PD: A Multi-Site Anonymized Clinical Dataset for Parkinson's Disease Gait Assessment
Vida Adeli, Ivan Klabucar, Javad Rajabi +25
Objective gait assessment in Parkinson's Disease (PD) is limited by the absence of large, diverse, and clinically annotated motion datasets. We introduce CARE-PD, the largest publi…
Detection of Chagas Disease from the ECG: The George B. Moody PhysioNet Challenge 2025
Matthew A. Reyna, Zuzana Koscova, Jan Pavlus +11
Objective: Chagas disease is a parasitic infection that is endemic to South America, Central America, and, more recently, the U.S., primarily transmitted by insects. Chronic Chagas…
FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep Stage Classification
Weitao Tang, Johann Vargas-Calixto, Nasim Katebi +5
Introduction: This study presents FetalSleepNet, the first published deep learning approach to classifying sleep states from the ovine electroencephalogram (EEG). Fetal EEG is comp…
Cross-Learning Between ECG and PCG: Exploring Common and Exclusive Characteristics of Bimodal Electromechanical Cardiac Waveforms
Sajjad Karimi, Amit J. Shah, Gari D. Clifford +1
Simultaneous electrocardiography (ECG) and phonocardiogram (PCG) provide a comprehensive, multimodal perspective on cardiac function by capturing the heart's electrical and mechani…
Fetal Sleep: A Cross-Species Review of Physiology, Measurement, and Classification
Weitao Tang, Johann Vargas-Calixto, Nasim Katebi +3
Study Objectives: Fetal sleep is a vital yet underexplored aspect of prenatal neurodevelopment. Its cyclic organization reflects the maturation of central neural circuits, and dist…
A Noise-Robust Model-Based Approach to T-Wave Amplitude Measurement and Alternans Detection
Zuzana Koscova, Amit Shah, Ali Bahrami Rad +3
T-wave alternans (TWA) is a potential marker for sudden cardiac death, but its reliable analysis is often constrained to noise-free environments, limiting its utility in real-world…
Auto-FEDUS: Autoregressive Generative Modeling of Doppler Ultrasound Signals from Fetal Electrocardiograms
Alireza Rafiei, Gari D. Clifford, Nasim Katebi
Fetal health monitoring through one-dimensional Doppler ultrasound (DUS) signals offers a cost-effective and accessible approach that is increasingly gaining interest. Despite its…
Edge AI for Real-time Fetal Assessment in Rural Guatemala
Nasim Katebi, Mohammad Ahmad, Mohsen Motie-Shirazi +14
Perinatal complications, defined as conditions that arise during pregnancy, childbirth, and the immediate postpartum period, represent a significant burden on maternal and neonatal…
Feasibility of Detecting Cognitive Impairment and Psychological Well-being among Older Adults Using Facial, Acoustic, Linguistic, and Cardiovascular Patterns Derived from Remote Conversations
Xiaofan Mu, Merna Bibars, Salman Seyedi +9
The aging society urgently requires scalable methods to monitor cognitive decline and identify social and psychological factors indicative of dementia risk in older adults. Our mac…
Electromechanical Dynamics of the Heart: A Study of Cardiac Hysteresis During Physical Stress Test
Sajjad Karimi, Shirin Karimi, Amit J. Shah +2
Cardiovascular diseases are best diagnosed using multiple modalities that assess both the heart's electrical and mechanical functions. While effective, imaging techniques like echo…
An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains
Jun Li, Aaron Aguirre, Junior Moura +6
Artificial intelligence (AI) has demonstrated significant potential in ECG analysis and cardiovascular disease assessment. Recently, foundation models have played a remarkable role…
ECG-Image-Database: A Dataset of ECG Images with Real-World Imaging and Scanning Artifacts; A Foundation for Computerized ECG Image Digitization and Analysis
Matthew A. Reyna, Deepanshi, James Weigle +10
We introduce the ECG-Image-Database, a large and diverse collection of electrocardiogram (ECG) images generated from ECG time-series data, with real-world scanning, imaging, and ph…
Feasibility of assessing cognitive impairment via distributed camera network and privacy-preserving edge computing
Chaitra Hegde, Yashar Kiarashi, Allan I Levey +3
INTRODUCTION: Mild cognitive impairment (MCI) is characterized by a decline in cognitive functions beyond typical age and education-related expectations. Since, MCI has been linked…
Explainable Artificial Intelligence for Quantifying Interfering and High-Risk Behaviors in Autism Spectrum Disorder in a Real-World Classroom Environment Using Privacy-Preserving Video Analysis
Barun Das, Conor Anderson, Tania Villavicencio +6
Rapid identification and accurate documentation of interfering and high-risk behaviors in ASD, such as aggression, self-injury, disruption, and restricted repetitive behaviors, are…
Benchmarking changepoint detection algorithms on cardiac time series
Ayse Cakmak, Erik Reinertsen, Shamim Nemati +1
The pattern of state changes in a biomedical time series can be related to health or disease. This work presents a principled approach for selecting a changepoint detection algorit…