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

Cognitive and Neurorehabilitation (262) Neurology and Neurosciences (185) Chronic Conditions (270) Digital Health, Telehealth and e-Innovation in Clinical Settings (401) Disabilities (116) Emerging Technologies for Rehabilitation (261) Technology in Physiotherapy (134)

Published on in Vol 9, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31164, first published .
The Association Between Actigraphy-Derived Behavioral Clusters and Self-Reported Fatigue in Persons With Multiple Sclerosis: Cross-sectional Study

The Association Between Actigraphy-Derived Behavioral Clusters and Self-Reported Fatigue in Persons With Multiple Sclerosis: Cross-sectional Study

The Association Between Actigraphy-Derived Behavioral Clusters and Self-Reported Fatigue in Persons With Multiple Sclerosis: Cross-sectional Study

Authors of this article:

Philipp Gulde1, 2 Author Orcid Image ;   Peter Rieckmann1 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Schmidle S, Gulde P, Koster R, Soaz C, Hermsdörfer J. The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults – a multicentric cross-sectional study. BMC Geriatrics 2023;23(1) View
  2. Gulde P, Vojta H, Schmidle S, Rieckmann P, Hermsdörfer J. Going beyond PA: Assessing sensorimotor capacity with wearables in multiple sclerosis—a cross-sectional study. Journal of NeuroEngineering and Rehabilitation 2023;20(1) View
  3. Dias M, Dörr F, Garthof S, Schäfer S, Elmers J, Schwed L, Linz N, Overell J, Hayward-Koennecke H, Tröger J, König A, Dillenseger A, Tackenberg B, Ziemssen T. Detecting fatigue in multiple sclerosis through automatic speech analysis. Frontiers in Human Neuroscience 2024;18 View