Can wearables warn us when we're getting sick? A community citsci project – open source & open data!

Local-first AI health assistant using wearable metrics, anomaly detection, and an Ollama LLM backend.

An Analysis on Depression using Actigraphy data

Personal website of Soha Niroumandi — PhD candidate at USC specializing in AI and biomechanics.

LSTM neural network for predicting health metrics from wearable sensor data. Full ML pipeline with data preprocessing, model training, and performance evaluation in R and Python.

The AI-Powered Health Monitoring System is designed to monitor users' health in real-time by leveraging data from wearable devices such as smartwatches and fitness trackers.

End-to-end ML pipeline for wearable stress detection using HRV and sleep data, featuring multimodal feature engineering, outlier detection, SMOTE balancing, ensemble learning, cross-validation, and predictive analytics.

A simple actigraphy processing pipeline for converting GENEActiv device files into CSV outputs for research analysis. The project includes device reading, preprocessing, epoch generation, sleep report export, and CSV comparison utilities.