The SOFAMEHACK team is happy to finally announce the winner of the first edition of the SOFAMEHACK organised by the SOFAMEA. We would like to thank all the 8 Participants who have submitted their works and shared their idea and technic for solving the problem of gait events detection in healthy and pathological gait. We are also very pleased to see that the participants ranged from master student to full-time researcher showing that research and work for our community is done at all level.
2019 SOFAMEA Winner: The Deep Event (Mathieu Lempereur)
The Deep Event algorithm developed by Mathieu Lempereur (research engineer at the CHRU of Brest) wins with an overall score of XX which correspond to a mean error between gold standard event and the one detected by his algorithm of 0.76 frames.
The proposed algorithm (Deep Event) is based on deep learning. The development of Deep Event was firstly based on his lab gait database containing more than 10 000 gait events. An article on proof of concepts and concurrent validity will be soon submitted to the Journal of Biomechanics.
Mathieu Lempereur will be awarded a prize of 1000 euros.
- Mathieu Lempereur (Deep Event) final score : 3,51
- Marc Desaules and Kieran Shubert (Data Mining) final score : 1.53 e+5
- Hugo Vili and Florent Moissenet (Joint Entropy) final score : 2.12 e+6
- Amyn Jaafar (Recurrent neural network) 6.53 e+6
- Team Kalf (Mean Learning) 25 e+77 (on some files no event was detected resulting in large errors)
The following team were not evaluated as they did not follow the challenge guide lines.
- Aurelia Autem and Gibran Chevalley
- Quentin Guy and Raphael
- Bigot Romain
As a reminder, as the full score is the sum of the exponential of the time differences between to the computed gait events and the gold-standard values of the gait events, even errors as low as 5 frames can increase importantly the final score.