This paper is in the following e-collection/theme issue:

Machine Learning (1501) Wearable Devices and Sensors (903) Decision Support for Health Professionals (1210) Clinical Information and Decision Making (1434) Osteoporosis and Osteoporosis Prevention (12) Falls Prevention in the Elderly (72) Falls and Emergency Detection with Sensors and other Technologies (37) Fitness Trackers and Smart Pedometers/Accelerometers (571)

Published on in Vol 10, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32724, first published .
Prediction of Physical Frailty in Orthogeriatric Patients Using Sensor Insole–Based Gait Analysis and Machine Learning Algorithms: Cross-sectional Study

Prediction of Physical Frailty in Orthogeriatric Patients Using Sensor Insole–Based Gait Analysis and Machine Learning Algorithms: Cross-sectional Study

Prediction of Physical Frailty in Orthogeriatric Patients Using Sensor Insole–Based Gait Analysis and Machine Learning Algorithms: Cross-sectional Study

Authors of this article:

Moritz Kraus1 Author Orcid Image ;   Maximilian Michael Saller1 Author Orcid Image ;   Sebastian Felix Baumbach1 Author Orcid Image ;   Carl Neuerburg1 Author Orcid Image ;   Ulla Cordula Stumpf1 Author Orcid Image ;   Wolfgang Böcker1 Author Orcid Image ;   Alexander Martin Keppler1 Author Orcid Image
Article Authors Cited by (15) Tweetations (4) Metrics

Moritz Kraus   1 ;   Maximilian Michael Saller   1 , Dr rer nat ;   Sebastian Felix Baumbach   1 , Dr med ;   Carl Neuerburg   1 , Dr med, PD ;   Ulla Cordula Stumpf   1 , Dr med ;   Wolfgang Böcker   1 , Prof Dr med ;   Alexander Martin Keppler   1 , Dr med

1 Department of Orthopaedics and Trauma Surgery, Musculoskeletal University Center Munich, Ludwig-Maximilians Universität Munich, Munich, Germany

Corresponding Author:

  • Alexander Martin Keppler, Dr med
  • Department of Orthopaedics and Trauma Surgery
  • Musculoskeletal University Center Munich
  • Ludwig-Maximilians Universität Munich
  • Marchioninistr. 15
  • Munich, 81377
  • Germany
  • Phone: 49 89-4400-0
  • Email: alexander.keppler@med.uni-muenchen.de