Trunk-pelvis coordination during load carriage running.

Understanding the influence of load carriage on trunk-pelvis coordination and its variability has important functional implications for athletes who need to run with load. The aim of this study was to examine the influence of load carriage on trunk-pelvis coordination in running. Thirty healthy adults performed running while wearing a 20% bodyweight backpack, and without load. Vector coding was used to quantify trunk-pelvis segmental coordination and its variability during the stance phase of running. The four coordination patterns were: 1) anti-phase (segments moving in opposite directions), in-phase (segments moving in same directions), trunk-only phase (only trunk movement), and pelvic-only phase (only pelvic movement). For each plane, the percentage of stance phase spent in a specific coordination pattern was quantified. Coordination variability for each plane was averaged over the stance phase. Mixed effects models were used to analyse the effects of load, adjusted for the covariate of sex, on coordination and its variability. Running with load increased trunk-only coordination in the sagittal plane (P < 0.001), increased anti-phase coordination in the frontal plane (P < 0.001), reduced trunk-only phase coordination in axial rotation (P < 0.001), and increased coordination variability in all three planes (Flexion-Extension: P < 0.001; Lateral flexion: P = 0.03; Axial rotation: P < 0.001). Future studies would benefit from investigating how trunk-pelvis coordination and its variability alters candidate end-point variability indices (e.g. COM displacement), and its functional implications in load carriage running

Performance of a lateral pelvic cluster technical system in evaluating running kinematics.

Valid measurement of pelvic and hip angles during posterior load carriage gait task requires placement of pelvic markers which will not be occluded or physically displaced by the load. One solution is the use of pure lateral pelvic clusters to track the pelvis segment. However, the validity of this method has not been compared against pelvic marker systems recommended by the International Society of Biomechanics (ISB) during high impact tasks, such as running. The purpose of this study was to validate the lateral tracking pelvic clusters against the ISB pelvis during running. Six participants performed overground running at a self-selected running speed with shoes. Three dimensional motion capture and synchronised in-ground force plates were used to determine lower limb joint angles and gait events respectively. Two biomechanical models were used to derive pelvic segment and hip joint angles. The ISB pelvis used the anterior and posterior iliac spines as anatomical and tracking markers, whilst the other model used lateral pelvic clusters as tracking markers. The between participant averaged coefficient of multiple correlation suggested good to excellent agreement between the angle waveforms generated from the two marker protocols. In addition, both marker protocols had similar sensitivity in detecting three dimensional pelvic and hip joint angles during the stance phase. This study suggests that in the event posterior load carriage is involved in running gait, pelvic and hip kinematics can be measured by the use of lateral pelvic clusters

Classifying individuals with and without patellofemoral pain syndrome using ground force profiles - Development of a method using functional data boosting.

BACKGROUND:Predictors of recovery in patellofemoral pain syndrome (PFPS) currently used in prognostic models are scalar in nature, despite many physiological measures originally lying on the functional scale. Traditional modelling techniques cannot harness the potential predictive value of functional physiological variables. RESEARCH QUESTION:What is the classification performance of PFPS status of a statistical model when using functional ground reaction force (GRF) time-series? METHODS:Thirty-one individuals (control = 17, PFPS = 14) performed maximal countermovement jumps, on two force plates. The three-dimensional components of the GRF profiles were time-normalized between the start of the eccentric phase and take-off, and used as functional predictors. A statistical model was developed using functional data boosting (FDboost), for binary classification of PFPS statuses (control vs PFPS). The area under the Receiver Operating Characteristic curve (AUC) was used to quantify the model's ability to discriminate the two groups. RESULTS:The three predictors of GRF waveform achieved an average out-of-bag AUC of 93.7 %. A 1 % increase in applied medial force reduced the log odds of being in the PFPS group by 0.68 at 87 % of jump cycle. In the AP direction, a 1 % reduction in applied posterior force increased the log odds of being classified as PFPS by 1.10 at 70 % jump cycle. For the vertical GRF, a 1 % increase in applied force reduced the log odds of being classified in the PFPS group by 0.12 at 44 % of the jump cycle. SIGNIFICANCE:Using simple functional GRF variables collected during functionally relevant task, in conjunction with FDboost, produced clinically interpretable models that retain excellent classification performance in individuals with PFPS. FDboost may be an invaluable tool to be used in longitudinal cohort prognostic studies, especially when scalar and functional predictors are collected

Quantifying lumbar mobility using a single tri-axial accelerometer

Background: Lumbar mobility is regarded as important for assessing and managing low back pain (LBP). Inertial Measurement Units (IMUs) are currently the most feasible technology for quantifying lumbar mobility in clinical and research settings. However, their gyroscopes are susceptible to drift errors, limiting their use for long-term remote monitoring. Research question: Can a single tri-axial accelerometer provide an accurate and feasible alternative to a multi-sensor IMU for quantifying lumbar flexion mobility and velocity? Methods: In this cross-sectional study, 18 healthy adults performed nine repetitions of full spinal flexion movements. Lumbar flexion mobility and velocity were quantified using a multi-sensor IMU and just the tri-axial accelerometer within the IMU. Correlations between the two methods were assessed for each percentile of the lumbar flexion movement cycle, and differences in measurements were modelled using a Generalised Additive Model (GAM). Results: Very high correlations (r &gt; 0.90) in flexion angles and velocities were found between the two methods for most of the movement cycle. However, the accelerometer overestimated lumbar flexion angle at the start (-4.7° [95 % CI -7.6° to -1.8°]) and end (-4.8° [95 % CI -7.7° to -1.9°]) of movement cycles, but underestimated angles (maximal difference of 4.3° [95 % CI 1.4° to 7.2°]) between 7 % and 92 % of the movement cycle. For flexion velocity, the accelerometer underestimated at the start (16.6°/s [95%CI 16.0 to 17.2°/s]) and overestimated (-12.3°/s [95%CI -12.9 to -11.7°/s]) at the end of the movement, compared to the IMU. Significance: Despite the observed differences, the study suggests that a single tri-axial accelerometer could be a feasible tool for continuous remote monitoring of lumbar mobility and velocity. This finding has potential implications for the management of LBP, enabling more accessible and cost-effective monitoring of lumbar mobility in both clinical and research settings

Quantifying lumbar mobility using a single tri-axial accelerometer

Background: Lumbar mobility is regarded as important for assessing and managing low back pain (LBP). Inertial Measurement Units (IMUs) are currently the most feasible technology for quantifying lumbar mobility in clinical and research settings. However, their gyroscopes are susceptible to drift errors, limiting their use for long-term remote monitoring. Research question: Can a single tri-axial accelerometer provide an accurate and feasible alternative to a multi-sensor IMU for quantifying lumbar flexion mobility and velocity? Methods: In this cross-sectional study, 18 healthy adults performed nine repetitions of full spinal flexion movements. Lumbar flexion mobility and velocity were quantified using a multi-sensor IMU and just the tri-axial accelerometer within the IMU. Correlations between the two methods were assessed for each percentile of the lumbar flexion movement cycle, and differences in measurements were modelled using a Generalised Additive Model (GAM). Results: Very high correlations (r &gt; 0.90) in flexion angles and velocities were found between the two methods for most of the movement cycle. However, the accelerometer overestimated lumbar flexion angle at the start (-4.7° [95 % CI -7.6° to -1.8°]) and end (-4.8° [95 % CI -7.7° to -1.9°]) of movement cycles, but underestimated angles (maximal difference of 4.3° [95 % CI 1.4° to 7.2°]) between 7 % and 92 % of the movement cycle. For flexion velocity, the accelerometer underestimated at the start (16.6°/s [95%CI 16.0 to 17.2°/s]) and overestimated (-12.3°/s [95%CI -12.9 to -11.7°/s]) at the end of the movement, compared to the IMU. Significance: Despite the observed differences, the study suggests that a single tri-axial accelerometer could be a feasible tool for continuous remote monitoring of lumbar mobility and velocity. This finding has potential implications for the management of LBP, enabling more accessible and cost-effective monitoring of lumbar mobility in both clinical and research settings

A comparison and update of direct kinematic-kinetic models of leg stiffness in human running

Direct kinematic-kinetic modelling currently represents the “Gold-standard” in leg stiffness quantification during three-dimensional (3D) motion capture experiments. However, the medial-lateral components of ground reaction force and leg length have been neglected in current leg stiffness formulations. It is unknown if accounting for all 3D would alter healthy biologic estimates of leg stiffness, compared to present direct modelling methods. This study compared running leg stiffness derived from a new method (multiplanar method) which includes all three Cartesian axes, against current methods which either only include the vertical axis (line method) or only the plane of progression (uniplanar method). Twenty healthy female runners performed shod overground running at 5.0 m/s. Three-dimensional motion capture and synchronised in-ground force plates were used to track the change in length of the leg vector (hip joint centre to centre of pressure) and resultant projected ground reaction force. Leg stiffness was expressed as dimensionless units, as a percentage of an individual's bodyweight divided by standing leg length (BW/LL). Leg stiffness using the line method was larger than the uniplanar method by 15.6%BW/LL (P &lt; .001), and multiplanar method by 24.2%BW/LL (P &lt; .001). Leg stiffness from the uniplanar method was larger than the multiplanar method by 8.5%BW/LL (6.5 kN/m) (P &lt; .001). The inclusion of medial-lateral components significantly increased leg deformation magnitude, accounting for the reduction in leg stiffness estimate with the multiplanar method. Given that limb movements typically occur in 3D, the new multiplanar method provides the most complete accounting of all force and length components in leg stiffness calculation