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Álvarez MN, Ruiz ARJ, Neira GGV, Huertas-Hoyas E, Cerda MTE, Delgado LP, Robles ER, Del-Ama AJ, Ruiz-Ruiz L, García-de-Villa S, Rodriguez-Sanchez C. Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor. Sci Rep 2023; 13:9208. [PMID: 37280388 DOI: 10.1038/s41598-023-36241-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/31/2023] [Indexed: 06/08/2023] Open
Abstract
Falls are one of the main concerns in the elderly population due to their high prevalence and associated consequences. Guidelines for the management of the elder with falls are comprised of multidimensional assessments, especially gait and balance. Daily clinical practice needs for timely, effortless, and precise tools to assess gait. This work presents the clinical validation of the G-STRIDE system, a 6-axis inertial measurement unit (IMU) with onboard processing algorithms, that allows the calculation of walking-related metrics correlated with clinical markers of fall risk. A cross-sectional case-control study was conducted with 163 participants (falls and non-falls groups). All volunteers were assessed with clinical scales and conducted a 15-min walking test at a self-selected pace while wearing the G-STRIDE. G-STRIDE is a low-cost solution to facilitate the transfer to society and clinical evaluations. It is open hardware and flexible and, thus, has the advantage of providing runtime data processing. Walking descriptors were derived from the device, and a correlation analysis was conducted between walking and clinical variables. G-STRIDE allowed measuring walking parameters in non-restricted walking conditions (e.g. hallway). Walking parameters statistically discriminate between falls and non-falls groups. We found good/excellent estimation accuracy (ICC = 0.885; [Formula: see text]) for walking speed, showing good/excellent correlation between gait speed and several clinical variables. G-STRIDE can calculate walking-related metrics that allow for discrimination between falls and non-falls groups, which correlates with clinical indicators of fall risk. A preliminary fall-risk assessment based on the walking parameters was found to improve the Timed Up and Go test in the identification of fallers.
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Affiliation(s)
- Marta Neira Álvarez
- Department of Geriatrics, Foundation for Research and Biomedical Innovation of the Infanta Sofía Hospital (HUIS), Madrid, 28702, Spain
| | - Antonio R Jiménez Ruiz
- Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain
| | | | - Elisabet Huertas-Hoyas
- Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine Department, Rey Juan Carlos University, Mostoles, 28933, Spain
| | | | | | | | - Antonio J Del-Ama
- School of Experimental Sciences and Technology, Rey Juan Carlos University, Mostoles, 28933, Spain
| | - Luisa Ruiz-Ruiz
- Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain
- Electronics Department, University of Alcalá (UAH), Alcalá de Henares, 28805, Spain
| | - Sara García-de-Villa
- Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain
- Electronics Department, University of Alcalá (UAH), Alcalá de Henares, 28805, Spain
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