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The implementation of inertial sensors for the assessment of temporal parameters of gait in the knee arthroplasty population
Institution:1. Department of Rehabilitation Sciences, KU Leuven Campus Bruges, Spoorwegstraat 12, 8200 Bruges, Belgium;2. Department of Rehabilitation Sciences, KU Leuven, Tervuursevest 101, 3001 Heverlee, Belgium;3. Department of Development and Regeneration, KULAK, Etienne Sabbelaan 53, 8500 Kortrijk, Belgium;4. Department of Computer Sciences, KU Leuven Campus Bruges, Spoorwegstraat 12, 8200 Bruges, Belgium;5. Department of Orthopaedic Surgery, AZ Sint-Lucas, Sint-Lucaslaan 29, 8310 Bruges, Belgium;1. Toronto Rehabilitation Institute–University Health Network, 550 University Ave, Toronto, Ontario M5G 2A2, Canada;2. School of Physical and Health Education, Nipissing University, 100 College Drive, North Bay, Ontario P1B 8L7, Canada;3. Evaluative Clinical Sciences, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, 2075 Bayview Ave, Toronto, Ontario M4N 3M5, Canada;4. Department of Physical Therapy, University of Toronto, 500 University Ave, Toronto, Ontario M5G 1V7, Canada
Abstract:BackgroundThe use of inertial measurement units for the evaluation of temporal parameters of gait has been studied in many populations. However, currently no studies support the use of inertial measurement units for this purpose in the knee arthroplasty population. The objective of the present study was to investigate the agreement between an inertial measurement and camera based system for the assessment of temporal gait parameters in a knee arthroplasty population.MethodsSixteen knee arthroplasty patients performed 3 gait trials at a self-selected speed along a 6 m walk-way. During the gait trials, gyroscope data from shank-worn inertial measurement units and motion data from optoelectronic cameras were collected simultaneously. A custom-made peak detection algorithm was used to identify gait events from gyroscope data, in order to compute cycle time, stance time and swing time. A marker and coordinate based algorithm was used to calculate temporal gait parameters from kinematical data derived from the camera system. Temporal variables were compared between both methods by calculating intra-class correlation coefficients, mean errors and root mean squared errors. Furthermore, Bland-Altman plots were constructed to assess the agreement between both methods.FindingsOverall good to excellent intra-class correlation values (0.826–0.972) were found. Root mean square errors between both methods ranged from 0.036 to 0.055 s. High levels of agreement were observed for all variables.InterpretationThese findings suggest that inertial measurement units can be used for outside laboratory assessment (e.g. in a hospital environment) of temporal gait parameters in the knee arthroplasty population.
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