PROJECTS

This project builds an intelligent agent that combines large language models with analytical tools to interpret physiological signals. Using the OpenCHA framework, the agent integrates user interaction, data pipelines, and health analytics to produce reliable insights from wearable data. In a case study on heart rate estimation from PPG signals, benchmarked against ECG as the gold standard, the agent achieves significantly lower error rates than GPT-4o and GPT-4o-mini. By bridging conversational AI with time-series analysis, this work demonstrates how LLM-powered agents can deliver accurate, scalable, and trustworthy health monitoring solutions.