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META DATA ANALYSIS LAB to Enhance Training Quality

Project description

Sweating to the beat of semantic analysis

More and more Europeans are inserting health-enhancing physical activity into their daily routine. To achieve better results, personal trainers strive to improve their competences and techniques, especially related to endurance training, rehabilitation and health precaution. Even though it is not easy, the existing amount of data from different fields could revolutionise training methods and bring new useful tools. The EU-funded MyGoalMEDAL project aims to engage machine learning in an interdisciplinary semantic analysis of existing international data from connected fields. The goal is to systemise metadata from all promising experiences, leading to disruptive innovations with new tools and applications for e-health and sports workouts.

Call for proposal

H2020-EIC-SMEInst-2018-2020

See other projects for this call

Sub call

H2020-SMEInst-2018-2020-1

Coordinator

PRIEBE MATHIAS
Net EU contribution
€ 50 000,00
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Other funding
€ 21 429,00