Literature highlights the need for research on changes in lumbar movement patterns, as potential mechanisms underlying the persistence of low-back pain. Variability and local dynamic stability are frequently used to characterize movement patterns. In view of a lack of information on reliability of these measures, we determined their within- and between-session reliability in repeated seated reaching. Thirty-six participants (21 healthy, 15 LBP) executed three trials of repeated seated reaching on two days. An optical motion capture system recorded positions of cluster markers, located on the spinous processes of S1 and T8. Movement patterns were characterized by the spatial variability (meanSD) of the lumbar Euler angles: flexion–extension, lateral bending, axial rotation, temporal variability (CyclSD) and local dynamic stability (LDE). Reliability was evaluated using intraclass correlation coefficients (ICC), coefficients of variation (CV) and Bland-Altman plots. Sufficient reliability was defined as an ICC ≥ 0.5 and a CV < 20%. To determine the effect of number of repetitions on reliability, analyses were performed for the first 10, 20, 30, and 40 repetitions of each time series. MeanSD, CyclSD, and the LDE had moderate within-session reliability; meanSD: ICC = 0.60–0.73 (CV = 14–17%); CyclSD: ICC = 0.68 (CV = 17%); LDE: ICC = 0.62 (CV = 5%). Between-session reliability was somewhat lower; meanSD: ICC = 0.44–0.73 (CV = 17–19%); CyclSD: ICC = 0.45–0.56 (CV = 19–22%); LDE: ICC = 0.25–0.54 (CV = 5–6%). MeanSD, CyclSD and the LDE are sufficiently reliable to assess lumbar movement patterns in single-session experiments, and at best sufficiently reliable in multi-session experiments. Within-session, a plateau in reliability appears to be reached at 40 repetitions for meanSD (flexion–extension), meanSD (axial-rotation) and CyclSD.
MULTIFILE
BackgroundIn adolescents with non-pathological and pathological joint hypermobility, gait deviations have been associated with pain and fatigue. It remains unclear what distinguishes the non-pathological form of joint hypermobility (JH) from pathological forms (i.e. hypermobile Ehlers-Danlos syndrome (hEDS) or hypermobility spectrum disorders (HSD). Our objective was to identify discriminative clinical characteristics and biomechanical gait features between adolescents with hEDS/HSD, JH, and healthy controls (HC).MethodsThirty-two adolescents were classified into three subgroups (hEDS/HSD=12, JH=5, HC=15). Clinical characteristics (e.g. pain intensity and surface, fatigue, functional disability) were inventoried.The gait pattern was assessed using a three-dimensional, eight-camera VICON MX1.3 motion capture system, operating at a sample rate of 100 Hz (VICON, Oxford, UK). Spatiotemporal parameters, joint angles (sagittal plane), joint work, joint impulse, ground reaction force and gait variability expressed as percentage using Principal Component Analysis (PCA) were assessed and analysed using multivariate analysis. Multivariate analysis data is expressed in mean differences(MD), standard error(SE) and P-values.ResultsThe hEDS/HSD-group had significantly higher fatigue score (+51.5 points, p = <0.001) and functional disability (+1.6, p < .001) than the HC-group. Pain intensity was significantly higher in the hEDS/HSD-group than the other subgroups (JH; +37 mm p = .004, HC; +38 mm, p = .001). The hEDS/HSD-group showed significantly more gait variability (JH; +7.2(2.0)% p = .003, HC; + 7.8(1.4)%, p = <0.001) and lower joint work (JH; −0.07(0.03)J/kg, p = .007, HC; − 0.06(0.03)J/kg, p = .013) than the other subgroups. The JH-group showed significantly increased ankle dorsiflexion during terminal stance (+5.0(1.5)degree, p = .001) compared to hEDS/HSD-group and knee flexion during loading response compared to HC-group (+5.7(1.8) degree, p = .011).SignificanceA distinctive difference in gait pattern between adolescents with non-pathological and pathological joint hypermobility is found in gait variability, rather than in the biomechanical features of gait. This suggests that a specific gait variability metric is more appropriate than biomechanical individual joint patterns for assessing gait in adolescents with hEDS/HSD.
Background: Osteoarthritis (OA) is the most common rheumatic disease of the musculoskeletal system, with the knee as the most affected joint. The number of people with OA of the knee is likely to increase due to the ageing society and the obesity epidemic. The predominant clinical symptom of knee OA is pain, which is described as worsening by activity and relieving by rest. Knee instability has been recognized as an important clinical feature in persons with knee OA. Pain and knee instability are associated with limitations in performing daily activities. Non-pharmacological options in the management of knee OA consist of education, weight loss, exercise, braces and physical therapy. Knee bracing has been recommended by the Osteoarthritis Research Society International (OARSI). Valgus knee braces designed to decrease loads on the medial compartment of the knee for patients with varus alignment are the most common. It has been shown however, that valgus bracing may have little or no effect on pain and physical functioning, and adherence to this treatment in patients with knee OA is low.Because of ease of use and access, lack of complications and low cost, soft knee braces are commonly used in persons with knee OA. However, the evidence for efficacy of soft knee bracing on pain and activity limitations in knee OA is limited. Therefore, it is important to strengthen the evidence of using a soft brace to reduce pain and activity limitations as well as to evaluate the efficacy of soft knee bracing on knee instability in persons with knee OA. There is also debate about the effectiveness of soft braces in other affected joints of the lower extremity and in conditions other than OA such as rheumatoid arthritis.Objectives: The aim of the study will be to evaluate the effect of wearing a soft brace on dynamic knee instability in patients with OA of the knee.Methods: Persons with knee OA and self-reported knee instability from the Amsterdam Osteoarthritis cohort participated in a single-session lab-experimental study. A within-subject design was used, comparing no brace versus brace, and comparing a non-tight versus a tight brace (standard fit). The primary outcome measure was dynamic knee instability, expressed by the Perturbation Response (PR), i.e., a biomechanics based measure reflecting deviation in the mean knee varus-valgus angle after a controlled mechanical perturbation, standardized to the mean (SD) varus-valgus angle during level walking. Linear mixed-effect model analysis was used to evaluate the effect of a brace on dynamic knee instability.Results: The wearing of a soft brace reduced the knee instability significantly during perturbed walking. Results will also be presented from the literature search and from the lab-experimental study.Conclusion: Wearing a soft brace reduces dynamic knee instability in patients with knee OA. However, longitudinal studies are needed to evaluate the clinical implications of wearing a soft brace.
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
