PROJECTS
Wearable Intelligence and Digital Biomarkers
This project develops AI methods that transform wearable and physiological signals into reliable digital biomarkers. Research includes PPG quality assessment, heart-rate estimation, circadian patterns, sleep EEG, and interpretable analysis of longitudinal sensor data.
- Reducing interdataset covariate shift in sleep EEG of traumatic brain injured humans and mice using transfer Euclidean alignment
- Circadian rhythm of heart rate and heart rate variability in pregnancy
- Multitask learning approach for PPG applications: Case studies on signal quality assessment and physiological parameters estimation
- An LLM-Powered Agent for Physiological Data Analysis: A Case Study on PPG-based Heart Rate Estimation
- Personalized Counterfactual Framework: Generating Potential Outcomes from Wearable Data
Project information
- Category: Health State Estimation and Personal Health Models
- Contact Person: Amir M. Rahmani
