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

Artificial Intelligence (122) Mobile Health (mhealth) (2777) Research Instruments, Questionnaires, and Tools (545) New Methods (911) Tools, Programs and Algorithms (245) Artificial Intelligence (1214) Fitness Trackers and Smart Pedometers/Accelerometers (543)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42337, first published .
A Trainable Open-Source Machine Learning Accelerometer Activity Recognition Toolbox: Deep Learning Approach

A Trainable Open-Source Machine Learning Accelerometer Activity Recognition Toolbox: Deep Learning Approach

A Trainable Open-Source Machine Learning Accelerometer Activity Recognition Toolbox: Deep Learning Approach

Authors of this article:

Fluri Wieland1 Author Orcid Image ;   Claudio Nigg1 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

Fluri Wieland   1 , BSc, MSc ;   Claudio Nigg   1 , BSc, MSc, PhD

1 Department of Health Science, Institute of Sports Science, University of Bern, Bern, Switzerland

Corresponding Author:

  • Fluri Wieland, BSc, MSc
  • Department of Health Science
  • Institute of Sports Science
  • University of Bern
  • Bremgartenstrasse 145
  • Bern, 3012
  • Switzerland
  • Phone: 41 787347220
  • Email: flu.wieland@gmail.com