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

AI in Older Adult Care (255) Longitudinal and Cohort Studies in Public Health (964) Machine Learning (3391) Frailty Detection, Assessment and Prediction (251) Biomechanics (65) AI Applications in Biomedical Engineering (44)

Published on in Vol 9 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/94597, first published .
Senior woman performing a squat during physical therapy session, monitored on laptop.

Machine Learning–Based Biomechanical and Clinical Assessment of the Five Times Chair Rise Test in Older Adults: Sensor-Based Functional Aging Study

Machine Learning–Based Biomechanical and Clinical Assessment of the Five Times Chair Rise Test in Older Adults: Sensor-Based Functional Aging Study

Authors of this article:

Anna Schumacher1 Author Orcid Image ;   Ole Meyer1, 2 Author Orcid Image ;   Vincent Quinten3 Author Orcid Image ;   Andreas Hein1 Author Orcid Image ;   Rebecca Diekmann3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Anna Schumacher   1 , Dr rer nat ;   Ole Meyer   1, 2 , MSc ;   Vincent Quinten   3 , MD, PhD ;   Andreas Hein   1 , Prof Dr-Ing ;   Rebecca Diekmann   3 , PD Dr oec troph

1 Assistance Systems and Medical Device Technology, School VI - Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Lower Saxony, Germany

2 OFFIS - Institute for Information Technology, Oldenburg, Lower Saxony, Germany

3 Junior Research Group “Nutrition and Physical Function in Older Adults”, School VI - Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Lower Saxony, Germany

Corresponding Author:

  • Anna Schumacher, Dr rer nat
  • Assistance Systems and Medical Device Technology, School VI - Medicine and Health Sciences
  • Carl von Ossietzky Universität Oldenburg
  • Ammerländer Heerstraße 140
  • Oldenburg, Lower Saxony 26129
  • Germany
  • Phone: 49 4417984630
  • Email: anna.schumacher@uni-oldenburg.de