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

Bioinformatics, genomics, tools and databases (17) Machine Learning (1465) Fitness Trackers and Smart Pedometers/Accelerometers (561) Innovations and Technology for Physical Activity Education (742)

Published on in Vol 3, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38512, first published .
Monitoring Physical Behavior in Rehabilitation Using a Machine Learning–Based Algorithm for Thigh-Mounted Accelerometers: Development and Validation Study

Monitoring Physical Behavior in Rehabilitation Using a Machine Learning–Based Algorithm for Thigh-Mounted Accelerometers: Development and Validation Study

Monitoring Physical Behavior in Rehabilitation Using a Machine Learning–Based Algorithm for Thigh-Mounted Accelerometers: Development and Validation Study

Authors of this article:

Frederik Skovbjerg1 Author Orcid Image ;   Helene Honoré1 Author Orcid Image ;   Inger Mechlenburg2 Author Orcid Image ;   Matthijs Lipperts3 Author Orcid Image ;   Rikke Gade4 Author Orcid Image ;   Erhard Trillingsgaard Næss-Schmidt1, 2 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Frederik Skovbjerg   1 , MSc ;   Helene Honoré   1 , MSc ;   Inger Mechlenburg   2 , DMSc ;   Matthijs Lipperts   3 , MSc ;   Rikke Gade   4 , PhD ;   Erhard Trillingsgaard Næss-Schmidt   1, 2 , PhD

1 Research Unit, Hammel Neurorehabilitation Centre & University Research Clinic, Hammel, Denmark

2 Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

3 Department of Medical Information and Communication Technology, St. Anna Hospital, Geldrop, Netherlands

4 Section of Media Technology, Aalborg University, Aalborg, Denmark

Corresponding Author:

  • Frederik Skovbjerg, MSc
  • Research Unit
  • Hammel Neurorehabilitation Centre & University Research Clinic
  • Voldbyvej 15
  • Hammel, 8450
  • Denmark
  • Phone: 45 28739264
  • Email: freskv@rm.dk