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

Development and Evaluation of Research Methods, Instruments and Tools (481) Registered Report (560) mHealth for Data Collection and Research (955) Tools, Programs and Algorithms (266) Fitness Trackers and Smart Pedometers/Accelerometers (561) Wearable Devices and Sensors (888) Formative Evaluation of Digital Health Interventions (2410) Mobile Health (mhealth) (2939) Implantable Wearable Devices and Body Extensions; Smart Prostheses (5) Wearable Devices and Sensors (26)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50035, first published .
Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study

Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study

Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study

Authors of this article:

Felix Kluge1 Author Orcid Image ;   Yonatan E Brand2 Author Orcid Image ;   M Encarna Micó-Amigo3 Author Orcid Image ;   Stefano Bertuletti4 Author Orcid Image ;   Ilaria D'Ascanio5 Author Orcid Image ;   Eran Gazit6 Author Orcid Image ;   Tecla Bonci7 Author Orcid Image ;   Cameron Kirk3 Author Orcid Image ;   Arne Küderle8 Author Orcid Image ;   Luca Palmerini5, 9 Author Orcid Image ;   Anisoara Paraschiv-Ionescu10 Author Orcid Image ;   Francesca Salis4 Author Orcid Image ;   Abolfazl Soltani10 Author Orcid Image ;   Martin Ullrich8 Author Orcid Image ;   Lisa Alcock3, 11 Author Orcid Image ;   Kamiar Aminian10 Author Orcid Image ;   Clemens Becker12, 13 Author Orcid Image ;   Philip Brown14 Author Orcid Image ;   Joren Buekers15, 16, 17 Author Orcid Image ;   Anne-Elie Carsin15, 16, 17 Author Orcid Image ;   Marco Caruso4 Author Orcid Image ;   Brian Caulfield18, 19 Author Orcid Image ;   Andrea Cereatti4 Author Orcid Image ;   Lorenzo Chiari5, 9 Author Orcid Image ;   Carlos Echevarria3, 20 Author Orcid Image ;   Bjoern Eskofier8 Author Orcid Image ;   Jordi Evers21 Author Orcid Image ;   Judith Garcia-Aymerich15, 16, 17 Author Orcid Image ;   Tilo Hache1 Author Orcid Image ;   Clint Hansen22 Author Orcid Image ;   Jeffrey M Hausdorff6, 23, 24, 25, 26 Author Orcid Image ;   Hugo Hiden14 Author Orcid Image ;   Emily Hume27 Author Orcid Image ;   Alison Keogh18, 19 Author Orcid Image ;   Sarah Koch15, 16, 17 Author Orcid Image ;   Walter Maetzler22 Author Orcid Image ;   Dimitrios Megaritis27 Author Orcid Image ;   Martijn Niessen21 Author Orcid Image ;   Or Perlman2, 23 Author Orcid Image ;   Lars Schwickert12 Author Orcid Image ;   Kirsty Scott7 Author Orcid Image ;   Basil Sharrack28, 29 Author Orcid Image ;   David Singleton18, 19 Author Orcid Image ;   Beatrix Vereijken30 Author Orcid Image ;   Ioannis Vogiatzis27 Author Orcid Image ;   Alison Yarnall3, 11, 14 Author Orcid Image ;   Lynn Rochester3, 11, 14 Author Orcid Image ;   Claudia Mazzà7 Author Orcid Image ;   Silvia Del Din3, 11 Author Orcid Image ;   Arne Mueller1 Author Orcid Image
Article Authors Cited by (2) Tweetations (10) Metrics

Journals

  1. Brand Y, Kluge F, Palmerini L, Paraschiv-Ionescu A, Becker C, Cereatti A, Maetzler W, Sharrack B, Vereijken B, Yarnall A, Rochester L, Del Din S, Muller A, Buchman A, Hausdorff J, Perlman O. Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults. Scientific Reports 2024;14(1) View
  2. Decker J, Boborzi L, Schniepp R, Jahn K, Wuehr M. Mobile Spatiotemporal Gait Segmentation Using an Ear-Worn Motion Sensor and Deep Learning. Sensors 2024;24(19):6442 View