Validation of an inertial sensor system for physical therapists to quantify movement coordination during functional tasks

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Deutscher übersetzter Titel:Validierung eines Inertialsensorsystems für Physiotherapeuten zur Quantifizierung der Bewegungskoordination bei funktionellen Aufgaben
Autor:Tulipani, Lindsey; Boocock, Mark G.; Lomond, Karen V.; El-Gohary, Mahmoud; Reid, Duncan A.; Henry, Sharon M.
Erschienen in:Journal of applied biomechanics
Veröffentlicht:34 (2018), 1, S. 23-30, Lit.
Format: Literatur (SPOLIT)
Publikationstyp: Zeitschriftenartikel
Medienart: Elektronische Ressource (online) Gedruckte Ressource
Sprache:Englisch
ISSN:1065-8483, 1543-2688
DOI:10.1123/jab.2016-0139
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Erfassungsnummer:PU201806004454
Quelle:BISp

Abstract des Autors

Physical therapists evaluate patients’ movement patterns during functional tasks; yet, their ability to interpret these observations consistently and accurately is unclear. Physical therapists would benefit from a clinic-friendly method for accurately quantifying movement patterns during functional tasks. Inertial sensors, which are inexpensive, portable sensors capable of monitoring multiple body segments simultaneously, are a relatively new rehabilitation technology. We sought to validate an inertial sensor system by comparing lower limb and lumbar spine kinematic data collected simultaneously with a commercial inertial sensor system and a motion camera system while 10 subjects performed functional tasks. Mean and peak segment angular displacement data were calculated and compared between systems. Mean angular displacement root mean square error between the systems across all tasks and segments was <5°. Mean differences in peak displacements were generally acceptable (<5°) for the femur, tibia, and pelvis segments for all tasks; however, the inertial system overestimated lumbar flexion compared to the motion camera system. These data suggest that the inertial system is capable of measuring angular displacements within 5° of a system widely accepted for its accuracy. Standardization of sensor placement, better attachment methods, and improvement of inertial sensor algorithms will further increase the accuracy of the system.