Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study

Constanze Dammeyer; Corina Nüesch; Rosa MS Visscher; Yong K Kim; Petros Ismailidis; Matthias Wittauer; Karl Stoffel; Yves Acklin; Christian Egloff; Cordula Netzer

Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study

Constanze Dammeyer, Corina Nüesch, Rosa MS Visscher, Yong K Kim, Petros Ismailidis, Matthias Wittauer, Karl Stoffel, Yves Acklin, Christian Egloff, Cordula Netzer

Careum School of Health

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	Journal of Orthopaedic Research®
Publication status	Published - 2024

Cite this

@article{4341a45e28164aa7b5ab91373e26e619,

title = "Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study",

author = "Constanze Dammeyer and Corina N{\"u}esch and Visscher, {Rosa MS} and Kim, {Yong K} and Petros Ismailidis and Matthias Wittauer and Karl Stoffel and Yves Acklin and Christian Egloff and Cordula Netzer",

year = "2024",

language = "English",

journal = "Journal of Orthopaedic Research{\textregistered}",

}

TY - JOUR

T1 - Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study

AU - Dammeyer, Constanze

AU - Nüesch, Corina

AU - Visscher, Rosa MS

AU - Kim, Yong K

AU - Ismailidis, Petros

AU - Wittauer, Matthias

AU - Stoffel, Karl

AU - Acklin, Yves

AU - Egloff, Christian

AU - Netzer, Cordula

PY - 2024

Y1 - 2024

M3 - Article

JO - Journal of Orthopaedic Research®

JF - Journal of Orthopaedic Research®

ER -