7 papers
When Derived Measurements Mislead: Quantifying and Mitigating LLM Over-Trust with Privileged-Modality Reliability Evidence
Zongheng Guo, Tao Chen, Tianli Li +6
The paper defines and quantifies derived-feature over‑trust (DFOT) where large language models treat derived measurements as direct facts, using physiological sensing (PPG vs. ECG)…
PG-LRF: Physiology-Guided Latent Rectified Flow for Electro-Hemodynamic PPG-to-ECG Generation
Xiaoda Wang, Minxiao Wang, Kaiqiao Han +10
Electrocardiography (ECG) is the clinical standard for cardiac assessment but requires dedicated hardware that does not scale to daily-life monitoring. Photoplethysmography (PPG) i…
SIGMA-PPG: Statistical-prior Informed Generative Masking Architecture for PPG Foundation Model
Zongheng Guo, Tao Chen, Yang Jiao +3
Current foundation model for photoplethysmography (PPG) signals is challenged by the intrinsic redundancy and noise of the signal. Standard masked modeling often yields trivial sol…
PPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation
Juntong Ni, Saurabh Kataria, Shengpu Tang +3
Photoplethysmography (PPG) is widely used in wearable health monitoring, yet large PPG foundation models remain difficult to deploy on resource-limited devices. We present PPG-Dist…
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…
Vision4PPG: Emergent PPG Analysis Capability of Vision Foundation Models for Vital Signs like Blood Pressure
Saurabh Kataria, Ayca Ermis, Lovely Yeswanth Panchumarthi +2
Photoplethysmography (PPG) sensor in wearable and clinical devices provides valuable physiological insights in a non-invasive and real-time fashion. Specialized Foundation Models (…