Detecting sleep deprivation from running biomechanics using machine learning classification: a comparison between wearable and laboratory motion capture
Frontiers in Bioengineering and Biotechnology · 2026
Abstract e pubblicazione originale
L’abstract è consultabile nella fonte originale. Non viene ripubblicato qui perché non risulta verificata una licenza compatibile.
Leggi nella fonte originale ↗Parole chiave
Sleep and Work-Related FatigueLower Extremity Biomechanics and PathologiesContext-Aware Activity Recognition Systemssleep deprivationrunning biomechanicswearable sensorsmotion capturetreadmill runninggait analysismachine learning classificationinterindividual variabilitystride-to-stride variabilityrunning injury riskendurance performance
Come citare questo studio
Maura Seynaeve, Kilian Hendrickx, Benedicte Vanwanseele, Toon T. de Beukelaar. (2026). Detecting sleep deprivation from running biomechanics using machine learning classification: a comparison between wearable and laboratory motion capture. Frontiers in Bioengineering and Biotechnology. DOI: 10.3389/fbioe.2026.1939545
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