Gait Parameters Can Be Derived Reliably and Validly from Augmented Reality Glasses in People with Parkinson’s Disease Performing 10-m Walk Tests at Comfortable and Fast Speeds
The 10-m walk test (10MWT) is a stopwatch-based clinical mobility assessment. To better understand mobility limitations, 10MWT test completion times may be complemented with gait parameters like step length. State-of-the-art augmented reality (AR) glasses can potentially do this given their unique 3D-positional data from which gait parameters may be derived. We examined the test-retest reliability, concurrent validity, and face validity of gait parameters derived from AR glasses during a 10MWT in 20 people with Parkinson's disease, performed at self-selected comfortable and fast-but-safe walking speeds. AR-derived 10MWT completion times and gait parameters (mean step length, cadence, and maximal gait speed) were compared across repetitions and with lab-based (Interactive Walkway) and clinical (stopwatch) reference systems. Good-to-excellent test-retest reliability statistics were observed for test completion times and gait parameters for all systems and conditions alike. Concurrent validity was demonstrated between AR, lab-based, and clinical references for test completion times (good-to-excellent agreement: ICC > 0.879) and gait parameters (excellent agreement: ICC > 0.942). Face validity was confirmed by significant differences in test completion times and gait parameters between speed conditions in a-priori expected directions. These findings support the conclusion that gait parameters can be derived reliably and validly from AR glasses in people with Parkinson's disease.
Authors
- Pieter F van Doorn (ORCID: https://orcid.org/0000-0002-3208-3475)
- Edward Nyman (ORCID: https://orcid.org/0000-0002-9425-5412)
- Daphne J. Geerse (ORCID: https://orcid.org/0000-0002-5277-6607)
- Melvyn Roerdink (ORCID: https://orcid.org/0000-0002-8534-1124)
- Eva M. Hoogendoorn (ORCID: https://orcid.org/0009-0005-4554-3628)
- Jara S. van Bergem (ORCID: https://orcid.org/0009-0007-4531-642X)
Institutions
- Maastricht University (NL)
- Vrije Universiteit Amsterdam (NL)
Publication Details
- Journal
- Sensors
- Published
- 2025-02-18
- DOI
- https://doi.org/10.3390/s25041230
- Citations
- 4
- Primary Topic
- Balance, Gait, and Falls Prevention
- Type
- article
- Field-Weighted Citation Impact
- 19.04
Funders
- UK Research and Innovation
- European Commission
- HORIZON EUROPE Framework Programme
- HORIZON EUROPE European Innovation Council