Introduction. 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. Methods. 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. Results. In total the subjects took 537 (41+/-8 mean+/-std) steps, 525 of which were correctly identified as step. 12 Steps were not detected, and 2 steps were incorrectly identified as step. Per subject the accuracy of the classification algorithm ranged from 57% to 97%. In only 2 subjects the accuracy was less than 75%, giving an overall accuracy of 85%. Discussion. In literature algorithms able to identify walking the stairs and normal walking have been reported with an accuracy in the range of 80–95%1,2. Our algorithm falls well within this range, and can be even further improved. The low accuracy in two subjects can be explained by the fact that the sensor was placed more to the front of the leg, which influences the low-pass horizontal acceleration. Using a combination of front-back and left-right acceleration could possibly solve this problem. In the future we are confident to identify also other activities and even distinguish different types of stair climbing (i.e. taking a step with each leg versus only taking steps with the unaffected leg and ‘dragging’ the second leg) and obtain more specific activity profiles to be used in clinical outcome assessment

Introduction. 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. Methods. 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. Results. During step-up FB-sway was higher for THA (20.4°±4.9) and TKA (21.7°±5.9) patients than for healthy controls (15.5°±3.4, p<0.001). Also asymmetry was higher (THA=20%, TKA=21%, H=11%, p<0.001). Results were similar during step down except for the affected leg of THA patients where FB-sway (THA=16.2°±3.0) was similar to controls but sign. different to TKA patients (22.2±4.4) producing a high diagnostic power (AUC=0.88) to differentiate THA and TKA. LR-sway was also indicative for THA patients being the only subjects showing high asymmetry between the legs (A=14.3°±3.7 vs UA=11.9°±3.1, p<0.001). Acceleration during step-down asymmetric in patients, especially in THA (H<TKA<THA;p<0.05; AUC=0.87). Discussion. The IMA-block-step test could detect pathology specific compensation mechanism: During step-up patients use more FB-sway (+29%) to generate momentum for compensating muscle weakness and decrease joint loading. During step-down, only THA patients showed less FB-sway with their affected leg avoiding the painful hip flexion. Also in THA the LR-sway was higher in the affected than unaffected side due to the typical abductor weakness and resulting Trendelenburg sign. The IMA-block-step test could objectify compensation mechanisms used in OA and showed the power to differentiate between H, TKA and THA. It is low cost and fast to perform (<5min) by non-specialist personnel and thus could be used in clinical routine to supplement questionnaire based outcome scores

In this study we quantified and characterised the return of functional mobility following open tibial fracture using the Hamlyn Mobility Score. A total of 20 patients who had undergone reconstruction following this fracture were reviewed at three-month intervals for one year. An ear-worn movement sensor was used to assess their mobility and gait. The Hamlyn Mobility Score and its constituent kinematic features were calculated longitudinally, allowing analysis of mobility during recovery and between patients with varying grades of fracture. The mean score improved throughout the study period. Patients with more severe fractures recovered at a slower rate; those with a grade I Gustilo-Anderson fracture completing most of their recovery within three months, those with a grade II fracture within six months and those with a grade III fracture within nine months.

Analysis of gait showed that the quality of walking continued to improve up to 12 months post-operatively, whereas the capacity to walk, as measured by the six-minute walking test, plateaued after six months.

Late complications occurred in two patients, in whom the trajectory of recovery deviated by > 0.5 standard deviations below that of the remaining patients. This is the first objective, longitudinal assessment of functional recovery in patients with an open tibial fracture, providing some clarification of the differences in prognosis and recovery associated with different grades of fracture.

Cite this article: Bone Joint J 2015; 97-B:1118–25.