Timeline
Here we summarize key dates and the competition timeline.
| Date | Event |
|---|---|
| 01/06/2026 | Phase 0: The data submission opens :op |
| 15/06/2026 | Phase 1: The submission portal for the familarization phase opens |
| 25/06/2026 | MUnitQuest Symposium at ISEK2026 (12:30 - 14:00, CET) |
| 15/09/2026 | Phase 0: The data submission system (Data challenge) closes (23:59, CET) |
| 30/06/2026 | Phase 1: The submission portal for the familarization phase closes |
| 15/10/2026 | Data evaluation completed |
| 01/11/2026 | Phase 2: The showdown phase starts by releasing the MUnitQuest data colletion |
| 31/12/2026 | Phase 2: The algorithm submission portal (Isometric and Dynamic challenge) closes (23:59, CET) |
| 15/01/2027 | The awards are announced and final leaderboards are published 🏆 |
Details about Phase 0 (Archive)
- Community members collect experimental and simulated HDsEMG data together with motor unit spike train labels
- Datasets need to be submitted through the data submission portal (see Data submission)
- As part of the Data challenge, an expert reviewer panel evaluates each dataset contribution
- Outstanding data contributions (top 5, rated by an expert reviewer panel) are invited to contribute to a special issue in the Journal of Electromyography and Kinesiology
- After the competition is completed, data is released on an open data repository (mandatory for datasets used in Phase 2, optional otherwise)
Details about Phase 1 (Familiarization)
- Runs parallel to Phase 0
- Competitors are provided with training data from the MUniverse benchmark collection (including motor unit spike train labels)
- Competitors develop and optimize their algorithms
- Participants can compete in both challenges (Isometric and Dynamic challenge) or in only one challenge
- To qualify for Phase 2, competitors need to upload their predictions (motor unit spike trains) through the algorithm submission portal (coming soon)
- Results from baseline algorithms (together with tutorials – coming soon) are provided for reference
- An anonymous preliminary leaderboard is provided as feedback
Details about Phase 2 (Showdown)
- Finals to determine the leaderboards of the Isometric challenge and the Dynamic challenge
- Competitors are provided with the MUnitQuest data collection (hidden labels) consisting of anonymized recordings collected in Phase 0
- Note that the organizers may make small alterations to the test data (e.g., injected noise, cropping signals, etc.) to limit the advantage of teams also participating in the Data challenge
- Submission of predicted motor unit spike trains
- To be eligible for awards, competitors need to share their code (e.g., using GitHub) openly