Accelerometers enable us to analyse gait outside conventional gait laboratories. Before these devices can be used in large scale studies and in clinical settings a thorough evaluation of their performance in different populations is required. The aim of this study was to present an acceleration-based reference database for healthy gait. The repeatability and inter-observer reliability of acceleration-based gait analysis was investigated. The sensitivity was tested on different age groups and the effect of gender was studied. A comprehensive set of gait parameters (i.e. cadence, speed, asymmetry and irregularity) were studied in 60 women and 60 men. Basic gait parameters showed high repeatability (VC(cadence) 1.51%, ICC(cadence) 0.996) and inter-observer reliability (ICC(cadence) 0.916), while asymmetry and irregularity showed lower repeatability (VC(asym) 47.88%, ICC(asym) 0.787) and inter-observer reliability (ICC(asym) 0.449). The effects of age and gender on gait parameters were found to be consistent with those reported in studies using other methodologies. These findings and the advantages of the device support the application of AGA for routine clinical use and in daily life.

This study investigated whether the Tinetti scale, as a subjective measure for fall risk, is associated with objectively measured gait characteristics. It is studied whether gait parameters are different for groups that are stratified for fall risk using the Tinetti scale. Moreover, the discriminative power of gait parameters to classify elderly according to the Tinetti scale is investigated. Gait of 50 elderly with a Tinneti>24 and 50 elderly with a Tinetti≤24 was analyzed using acceleration-based gait analysis. Validated algorithms were used to derive spatio-temporal gait parameters, harmonic ratio, inter-stride amplitude variability and root mean square (RMS) from the accelerometer data. Clear differences in gait were found between the groups. All gait parameters correlated with the Tinetti scale (r-range: 0.20-0.73). Only walking speed, step length and RMS showed moderate to strong correlations and high discriminative power to classify elderly according to the Tinetti scale. It is concluded that subtle gait changes that have previously been related to fall risk are not captured by the subjective assessment. It is therefore worthwhile to include objective gait assessment in fall risk screening.

: Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Gait impairments are common among people with PD. Wearable sensor systems can be used for gait analysis by providing spatio-temporal parameters useful to investigate the progression of gait problems in Parkinson disease. However, various methods and tools with very high variability have been developed. The aim of this study is to review published articles of the last 10 years (from 2008 to 2018) concerning the application of wearable sensors to assess spatio-temporal parameters of gait in patients with PD. We focus on inertial sensors used for gait analysis in the clinical environment (i.e., we do not cover the use of inertial sensors to monitor walking or general activities at home, in unsupervised environments). Materials and Methods: Relevant articles were searched in the Medline database using Pubmed. Results and Discussion: Two hundred ninety-four articles were initially identified while searching the scientific literature regarding this topic. Thirty-six articles were selected and included in this review. Conclusion: Wearable motion sensors are useful, non-invasive, low-cost, and objective tools that are being extensively used to perform gait analysis on PD patients. Being able to diagnose and monitor the progression of PD patients makes wearable sensors very useful to evaluate clinical efficacy before and after therapeutic interventions. However, there is no uniformity in the use of wearable sensors in terms of: number of sensors, positioning, chosen parameters, and other characteristics. Future research should focus on standardizing the measurement setup and selecting which spatio-temporal parameters are the most informative to analyze gait in PD. These parameters should be provided as standard assessments in all studies to increase replicability and comparability of results.

We have investigated the accuracy of the templating of digital radiographs in planning total hip replacement using two common object-based calibration methods with the ball placed laterally (method 1) or medially (method 2) and compared them with two non-object-based methods. The latter comprised the application of a fixed magnification of 121% (method 3) and calculation of magnification based on the object-film-distance (method 4). We studied the post-operative radiographs of 57 patients (19 men, 38 women, mean age 73 years (53 to 89)) using the measured diameter of the prosthetic femoral head and comparing it with the true value. Both object-based methods (1 and 2) produced large errors (mean/maximum: 2.55%/17.4% and 2.04%/6.46%, respectively). Method 3 applying a fixed magnification and method 4 (object-film-distance) produced smaller errors (mean/maximum 1.42%/5.22% and 1.57%/4.24%, respectively; p < 0.01). The latter results were clinically relevant and acceptable when planning was allowed to within one implant size. Object-based calibration (methods 1 and 2) has fundamental problems with the correct placement of the calibration ball. The accuracy of the fixed magnification (method 3) matched that of object-film-distance (method 4) and was the most reliable and efficient calibration method in digital templating.

An inertial measurement unit (IMU) allows kinematic evaluation of human motion with fewer operational constraints than a gold standard optoelectronic motion capture (MOCAP) system. The study's aim was to compare IMU and MOCAP measurements of dynamic pelvic orientation angles during different activities of daily life (ADL): gait, sit-to-stand (STS) transfers and block step-up (BS) transfers. A single IMU was attached onto the lower back in seventeen healthy participants (8F/9 M, age 19-31 years; BMI < 25) and optical skin markers were attached onto anatomical pelvic landmarks for MOCAP measurements. Comparisons between IMU and MOCAP by Bland-Altman plots demonstrated that measurements were between 2SD of the absolute difference and Pearson's correlation coefficients were between 0.85 and 0.94. Frontal plane pelvic angle estimations achieved a RMSE in the range of [2.7°-4.5°] and sagittal plane measurements achieved a RMSE in the range of [2.7°-8.9°] which were both lowest in gait. Waveform peak detection times demonstrated ICCs between 0.96 and 1.00. These results are in accordance to other studies comparing IMU and MOCAP measurements with different applications and suggest that an IMU is a valid tool to measure dynamic pelvic angles during various activities of daily life which could be applied to monitor rehabilitation in a wide variety of musculoskeletal disorders.

In hemiarthroplasty of the hip using current generation stems, cemented stems result in fewer implant-related complications and similar mortality compared with cementless stems. Cite this article: 2017;99-B:421-31.

No abstract

SummaryBackground/ObjectiveActivity is increasingly being recognized as a highly relevant parameter in all areas of healthcare for diagnosis, treatment, or outcome assessment, especially in orthopaedics where the movement apparatus is directly affected. Therefore, the aim of this study was to develop, describe, and clinically validate a generic activity-monitoring algorithm, satisfying a combination of three criteria. The algorithm must be able to identify, count, and time a large set of relevant daily activities. It must be validated for orthopaedic patients as well as healthy individuals, and the validation must be in a setting that mimics free-living conditions.MethodsUsing various technical solutions, such as a dual-axis approach, dynamic inclinometry (hip flexion), and semiautomatic calibration (gait speed), the algorithms were designed to count and time the following postures, transfers, and activities of daily living: resting/sitting, standing, walking, ascending and descending stairs, sit–stand transitions, and cycling. In addition, the number of steps per walking bout was determined. Validation was performed with healthy individuals and patients who had undergone unilateral total joint arthroplasty, representing a wide spectrum of functional capacity. Video observation was used as the gold standard to count and time activities in a validation protocol approaching free-living conditions.ResultsIn total 992 and 390 events (activities or postures) were recorded in the healthy group and patient group, respectively. The mean error varied between 0% and 2.8% for the healthy group and between 0% and 7.5% for the patient group. The error expressed in percentage of time varied between 2.0% and 3.0% for both groups.ConclusionActivity monitoring of orthopaedic patients by counting and timing a large set of relevant daily life events is feasible in a user- and patient-friendly way and at high clinical validity using a generic three-dimensional accelerometer and algorithms based on empirical and physical methods. The algorithms performed well for healthy individuals as well as patients recovering after total joint replacement in a challenging validation set-up. With such a simple and transparent method real-life activity parameters can be collected in orthopaedic practice for diagnostics, treatments, outcome assessment, or biofeedback.