Inertial sensor motion analysis of gait, sit–stand transfers and step-up transfers: differentiating knee patients from healthy controls

Abstract

Patients undergoing total knee replacement for end stage knee osteoarthritis (OA) become increasingly younger and more demanding. Consequently, outcome assessment tools need to evolve toward objective performance-based measures. We applied a novel approach toward ambulatory biomechanical assessment of physical function using a single inertial sensor located at the pelvis to derive various motion parameters during activities of daily living. We investigated the potential of a clinically feasible battery of tests to define relevant parameters of physical function. We compared preoperative measures of end stage knee OA patients to healthy subjects. Our results show that measures of time yield the highest discriminative capacity to differentiate between groups. Additionally we found disease-dependent and task-specific alterations of movement for inertial sensor-derived motion parameters with good discriminative capacity. The inertial sensor's output quantities seem to capture another clinically relevant dimension of physical function that is supplementary to time. This study demonstrates the potential of inertial sensor-based motion analysis and provides a standardized test feasible for a routine clinical application in the longitudinal follow-up.

Pelvic movement strategies and leg extension power in patients with end-stage medial compartment knee osteoarthritis: a cross-sectional study

“…This is in accordance with the results reported in a study of healthy, young subjects [41]. Also in line with the present findings, Bolink et al [14] reported significantly greater pROM for controls than for patients. Of note, however, their patients walked significantly slower than the controls, which may have affected the pROM since no adjustment was made.…”

“…Data was sampled at 100 Hz. The IMU measured trunk acceleration and angular pelvic motion in three dimensions [14], and via algorithms in MatLab 7.10.0 Ò spatio-temporal estimates of pelvic range of motion could be derived [14,[32][33][34]. Range of motion was calculated as the mean difference between minimum and maximum angular pelvic motion.…”

“…Three repetitions of stepping up and down with one leg were followed by three repetitions of stepping up and down with the other leg [14]. Subjects had to be able to complete at least three steps with each leg before the test was included for further analysis.…”

“…Pelvic movement strategies during walking have only been sparsely investigated [9,13], and we found no studies evaluating pelvic movement strategies for patients with medial compartment knee OA during more advanced tasks such as stair climbing and stepping onto a step. Patients with knee OA report problems with these activities [14], which could lead to compensatory strategies. Further investigation into differences in movements between patients and healthy controls during stair climbing and stepping could identify target areas for rehabilitation programs.…”

Improving patients’ experience and outcome of total joint replacement: the RESTORE programme

“…The table also provides an overview of the ICF domains included within each functional assessment measure, with classification of self-completed PROMs and clinician-administered measures based on the results of an expert consensus study by Pollard and colleagues 60 We also conducted a gait analysis using a single inertial sensor to derive motion parameters during ADL. 305 There are a number of other measures that could have been included in this study such as the OHS and OKS, 117,274 HSS, 113 KOOS 306 and NHP. 307 However, to avoid participation burden and fatigue only a selection of measures was chosen.…”