1 citations · 1 across the 4 of their papers we have counts for
4 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…
Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signals
Saurabh Kataria, Yi Wu, Zhaoliang Chen +21
Foundation models are large-scale machine learning models that are pre-trained on massive amounts of data and can be adapted for various downstream tasks. They have been extensivel…
GPT-PPG: A GPT-based Foundation Model for Photoplethysmography Signals
Zhaoliang Chen, Cheng Ding, Saurabh Kataria +4
This study introduces a novel application of a Generative Pre-trained Transformer (GPT) model tailored for photoplethysmography (PPG) signals, serving as a foundation model for var…
SiamQuality: A ConvNet-Based Foundation Model for Imperfect Physiological Signals
Cheng Ding, Zhicheng Guo, Zhaoliang Chen +3
Foundation models, especially those using transformers as backbones, have gained significant popularity, particularly in language and language-vision tasks. However, large foundati…