In orthopaedics, clinical outcome assessment (COA) is still mostly performed by questionnaires which suffer from subjectivity, a ceiling effect and pain dominance. Real life activity monitoring (AM) holds the promise to become the new standard in COA with small light weight and easy to use accelerometers. More and more activities can be identified by algorithms based on accelerometry. The identification of stair climbing for instance is important to assess the participation of patients in normal life after an orthopaedic procedure. In this study we validated a custom made algorithm to distinguish normal gait, ascending and descending stairs on a step by step basis. A small, lightweight 3D-accelerometer taped to the lateral side of the affected (patients) or non-dominant (healthy subjects) upper leg served as the activity monitor. 13 Subjects (9 patients, 4 healthy) walked a few steps before descending a flight stairs (20 steps with a 180o turn in the middle), walked some steps more, turned around and ascended the same stairs. Templates (up, down and level) were obtained by averaging and stretching the vertical acceleration in the 4 healthy subjects. Classification parameters (low pass (0.4 Hz) horizontal (front-back) acceleration and the Euclidian distance between the vertical acceleration and each template) were obtained for each step. Accuracy is given by the percentage of correctly classified steps.Introduction
Methods
Our classic outcome scores increasingly fail to distinguish interventions or to reflect rising patient demands. Scores are subjective, have a low ceiling and score pain rather than function. Objective functional assessment tools for routine clinical use are required. This study validates inertial sensor motion analysis (IMA) by differentiating patients with knee versus hip osteoarthritis in a block-step test. Step up and down from a block (h=20cm, 3 repetitions) loading the affected (A) and unaffected (UA) leg was measured in n=59 subjects using a small inertial sensor (3D gyro and accelerometer, m=39g) attached onto the sacrum. Patients indicated for either primary unilateral THA (n=20; m/f=4/6, age=69.4yrs ±9.8) or TKA (n=16;m/f=7/9;age=67.8yrs ±8.2) were compared to healthy controls (n=23;m/f=13/10;age=61.7yrs ±6.2) and between each other to validate the test's capacity for diagnostics and as an outcome measure. The motion parameters derived (semi-) automatically in Matlab for both legs were: front-back (FB-) sway and left-right (LR-) sway (up and down); peak-to-peak accelerations (Acc) during step down. In addition the asymmetry between both legs (ASS) was calculated for each parameter. Group differences were tested (t-test) and the diagnostic value determined by the area under the curve (AUC) of the ROC-curve.Introduction
Methods
