User guide

Build a sleepKIT workflow from datasets, feature extraction and model architectures. Use the guides below to configure each step, then follow a tutorial for a complete experiment.

Run an experiment

Start with a task configuration and work through the modes you need.

Configure a run Download data Train Evaluate Export Run a demo

Choose your components

• Datasets provide recordings and labels for your task. Review each dataset’s access requirements and terms.
• Feature sets transform recordings into inputs for training and evaluation.
• Model architectures define the network and its configurable parameters.

Browse datasets Explore feature sets Choose an architecture

Tutorials and experiments

Train a sleep-detection model from wrist IMU data in the saved notebook, or explore how feature and model choices affect sleep staging.

Detection training notebook Staging ablation study