NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semantic, and taxonomic correlations between EEG electrode locations and brain regions, resulting in improved accuracy. Presented at PAKDD '24.

The W4H Integrated Toolkit Repository provides a unified platform for managing, analyzing, and visualizing wearable health data using a suite of open-source tools and frameworks.

StreamSim is a versatile real-time data streaming simulator tool for researchers and developers that enables the simulation of real-time streaming behavior for tabular data, facilitating comprehensive testing of real-time applications.

Python library for seamless interaction with Garmin API, enabling fetching of activity and health data using Garmin Pull API.

🌉 W4H ImportHub - An intuitive tool designed to effortlessly bridge the gap between your offline datasets and the W4H platform. From seamless CSV integration to smart data mappings, step into the expansive world of W4H with ease.

Postgres Extension for Answering Approximate Aggregate Queries on Time Series Data