Scientific Reports (Jan 2024)
Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device
- Cameron Kirk,
- Arne Küderle,
- M. Encarna Micó-Amigo,
- Tecla Bonci,
- Anisoara Paraschiv-Ionescu,
- Martin Ullrich,
- Abolfazl Soltani,
- Eran Gazit,
- Francesca Salis,
- Lisa Alcock,
- Kamiar Aminian,
- Clemens Becker,
- Stefano Bertuletti,
- Philip Brown,
- Ellen Buckley,
- Alma Cantu,
- Anne-Elie Carsin,
- Marco Caruso,
- Brian Caulfield,
- Andrea Cereatti,
- Lorenzo Chiari,
- Ilaria D’Ascanio,
- Judith Garcia-Aymerich,
- Clint Hansen,
- Jeffrey M. Hausdorff,
- Hugo Hiden,
- Emily Hume,
- Alison Keogh,
- Felix Kluge,
- Sarah Koch,
- Walter Maetzler,
- Dimitrios Megaritis,
- Arne Mueller,
- Martijn Niessen,
- Luca Palmerini,
- Lars Schwickert,
- Kirsty Scott,
- Basil Sharrack,
- Henrik Sillén,
- David Singleton,
- Beatrix Vereijken,
- Ioannis Vogiatzis,
- Alison J. Yarnall,
- Lynn Rochester,
- Claudia Mazzà,
- Bjoern M. Eskofier,
- Silvia Del Din,
- Mobilise-D consortium
Affiliations
- Cameron Kirk
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
- Arne Küderle
- Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg
- M. Encarna Micó-Amigo
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
- Tecla Bonci
- Department of Mechanical Engineering and Insigneo Institute for in Silico Medicine, The University of Sheffield
- Anisoara Paraschiv-Ionescu
- Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne
- Martin Ullrich
- Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg
- Abolfazl Soltani
- Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne
- Eran Gazit
- Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center
- Francesca Salis
- Department of Biomedical Sciences, University of Sassari
- Lisa Alcock
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
- Kamiar Aminian
- Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne
- Clemens Becker
- Robert Bosch Gesellschaft für Medizinische Forschung
- Stefano Bertuletti
- Department of Biomedical Sciences, University of Sassari
- Philip Brown
- The Newcastle Upon Tyne Hospitals NHS Foundation Trust
- Ellen Buckley
- Department of Mechanical Engineering and Insigneo Institute for in Silico Medicine, The University of Sheffield
- Alma Cantu
- School of Computing, Newcastle University
- Anne-Elie Carsin
- Barcelona Institute for Global Health (ISGlobal)
- Marco Caruso
- Department of Electronics and Telecommunications, Politecnico di Torino
- Brian Caulfield
- Insight Centre for Data Analytics, University College Dublin
- Andrea Cereatti
- Department of Electronics and Telecommunications, Politecnico di Torino
- Lorenzo Chiari
- Department of Electrical, Electronic and Information Engineering «Guglielmo Marconi», University of Bologna
- Ilaria D’Ascanio
- Department of Electrical, Electronic and Information Engineering «Guglielmo Marconi», University of Bologna
- Judith Garcia-Aymerich
- Barcelona Institute for Global Health (ISGlobal)
- Clint Hansen
- Department of Neurology, University Medical Center Schleswig-Holstein Campus Kiel
- Jeffrey M. Hausdorff
- Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center
- Hugo Hiden
- The Newcastle Upon Tyne Hospitals NHS Foundation Trust
- Emily Hume
- Department of Sport, Exercise and Rehabilitation, Northumbria University Newcastle
- Alison Keogh
- Insight Centre for Data Analytics, University College Dublin
- Felix Kluge
- Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg
- Sarah Koch
- Barcelona Institute for Global Health (ISGlobal)
- Walter Maetzler
- Department of Neurology, University Medical Center Schleswig-Holstein Campus Kiel
- Dimitrios Megaritis
- Department of Sport, Exercise and Rehabilitation, Northumbria University Newcastle
- Arne Mueller
- Novartis Institutes of Biomedical Research, Novartis Pharma AG
- Martijn Niessen
- McRoberts BV
- Luca Palmerini
- Department of Electrical, Electronic and Information Engineering «Guglielmo Marconi», University of Bologna
- Lars Schwickert
- Robert Bosch Gesellschaft für Medizinische Forschung
- Kirsty Scott
- Department of Mechanical Engineering and Insigneo Institute for in Silico Medicine, The University of Sheffield
- Basil Sharrack
- Department of Neuroscience and Sheffield NIHR Translational Neuroscience BRC, Sheffield Teaching Hospitals NHS Foundation Trust
- Henrik Sillén
- Digital Health R&D
- David Singleton
- Insight Centre for Data Analytics, University College Dublin
- Beatrix Vereijken
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology
- Ioannis Vogiatzis
- Department of Sport, Exercise and Rehabilitation, Northumbria University Newcastle
- Alison J. Yarnall
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
- Lynn Rochester
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
- Claudia Mazzà
- Department of Mechanical Engineering and Insigneo Institute for in Silico Medicine, The University of Sheffield
- Bjoern M. Eskofier
- Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg
- Silvia Del Din
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
- Mobilise-D consortium
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
- DOI
- https://doi.org/10.1038/s41598-024-51766-5
- Journal volume & issue
-
Vol. 14,
no. 1
pp. 1 – 23
Abstract
Abstract This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987.
