30 citations · 79 across the 5 of their papers we have counts for
5 papers
A Comprehensive Inference-Time Augmentation Framework in Physiological Signals: Application to PPG-Based AF Detection
Davood Fattahi, Runze Yan, Saurabh Kataria +2
Objective: Accurate classification of physiological signals in real-world deployments is challenged by sensor noise, motion artifacts, and distribution shifts between training and…
Wav2Arrest 2.0: Long-Horizon Cardiac Arrest Prediction with Time-to-Event Modeling, Identity-Invariance, and Pseudo-Lab Alignment
Saurabh Kataria, Davood Fattahi, Minxiao Wang +5
High-frequency physiological waveform modality offers deep, real-time insights into patient status. Recently, physiological foundation models based on Photoplethysmography (PPG), s…
Noisy Neonatal Chest Sound Separation for High-Quality Heart and Lung Sounds
Ethan Grooby, Chiranjibi Sitaula, Davood Fattahi +8
Stethoscope-recorded chest sounds provide the opportunity for remote cardio-respiratory health monitoring of neonates. However, reliable monitoring requires high-quality heart and…
Real-Time Multi-Level Neonatal Heart and Lung Sound Quality Assessment for Telehealth Applications
Ethan Grooby, Chiranjibi Sitaula, Davood Fattahi +8
Digital stethoscopes in combination with telehealth allow chest sounds to be easily collected and transmitted for remote monitoring and diagnosis. Chest sounds contain important in…
A New Non-Negative Matrix Co-Factorisation Approach for Noisy Neonatal Chest Sound Separation
Ethan Grooby, Jinyuan He, Davood Fattahi +6
Obtaining high-quality heart and lung sounds enables clinicians to accurately assess a newborn's cardio-respiratory health and provide timely care. However, noisy chest sound recor…