Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty

Kluge F, Hannink J, Pasluosta CF, Klucken J, Gaßner H, Gelse K, Eskofier B, Krinner S (2018)

Publication Type: Journal article, Original article

Publication year: 2018

Journal

Gait & Posture Elsevier

Book Volume: 66

Pages Range: 194-200

URI: https://www.mad.tf.fau.de/files/2020/12/kluge_2018_gp_proof.pdf

DOI: 10.1016/j.gaitpost.2018.08.026

Authors with CRIS profile

Felix Kluge Julius Hannink Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Jochen Klucken Medizinische Fakultät Heiko Gaßner Department of Molecular Neurology Kolja Gelse Björn Eskofier Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics)

Additional Organisation(s)

Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Machine Learning and Data Analytics Lab

Related research project(s)

EFI Moves: Individualized Diagnosis and Treatment in motion (EFIMoves) Jan. 1, 2014 - Dec. 31, 2017

Involved external institutions

Albert-Ludwigs-Universität Freiburg DE Germany (DE)

How to cite

APA:

Kluge, F., Hannink, J., Pasluosta, C.F., Klucken, J., Gaßner, H., Gelse, K.,... Krinner, S. (2018). Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty. Gait & Posture, 66, 194-200. https://doi.org/10.1016/j.gaitpost.2018.08.026

MLA:

Kluge, Felix, et al. "Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty." Gait & Posture 66 (2018): 194-200.

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