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Classification system for Ai-enabled consumer-grade wearable technologies aiming to automatize decision-making about individualization of exercise procedures
Department of Sports Science and Movement Pedagogy, Technische Universität Braunschweig, Braunschweig, Germany.
Institute for Health & Sport, Victoria University, Melbourne, VIC, Australia.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements. Department of Physiology and Pharmacology, Biomedicum C5, Karolinska Institutet, Stockholm, Sweden.ORCID iD: 0000-0002-3814-6246
Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Braunschweig, Germany.
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2025 (English)In: Frontiers in Sports and Active Living, E-ISSN 2624-9367, Vol. 6, article id 1500563Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2025. Vol. 6, article id 1500563
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Artificial Intelligence
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Machine Elements
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URN: urn:nbn:se:ltu:diva-113976DOI: 10.3389/fspor.2024.1500563ISI: 001419331800001PubMedID: 39945004Scopus ID: 2-s2.0-85219144138OAI: oai:DiVA.org:ltu-113976DiVA, id: diva2:1980909
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Full text license: CC BY 4.0;

Available from: 2025-07-03 Created: 2025-07-03 Last updated: 2025-07-03

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Holmberg, Hans-Christer

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