1,721,038 research outputs found
Calculating centre of pressure from multiple force plates for kinetic analysis of sprint running
No full textForce plates are relatively small compared to athletes’ step lengths during sprint running. A large number of trials are subsequently rejected when collecting force plate data, which could be reduced by using multiple force plates. The aim of this study was to determine the suitability of foot contacts occurring across the boundaries of two force plates for use in inverse dynamics analyses. Centre of pressure data for a loaded wheel rolling across two force plates were compared to known positions of the wheel measured using an automated motion analysis system. A mean difference of 0.0027 [±0.0024] m was found between centre of pressure location and the measured wheel position as the wheel crossed the boundary between plates. The centre of pressure error resulted in joint power errors ranging from 0.27% to 1.47% for the ankle, knee and hip
Surface Electrode Array based Control of the Wrist and Hand
No full textSurface stimulation is a non-invasive method of muscle activation that uses adhesive electrodes placed on the surface of the patient skin above thelocation of the desired muscles. One application is in stroke rehabilitation where a controller is used to provide assistive stimulation to a patient completing a finite duration task with the impaired limb. Effectiveness of treatment is strongly related to the precision and accuracy of the stimulation applied, and the feasibility of advanced control approaches has been established in two recent clinical trials using iterative learning control algorithms.Commercially available large surface electrodes are not suitable for precise control of the hand and wrist due to their weak selectivity and simultaneous activation of several opposing muscles. An alternative is the use of electrode arrays where individual array element selection enables more precise control of muscle activation. Locating the optimal stimulation sites is critical to the effective application of surface electrode array stimulation and this paper develops a method for optimal selection of the stimulation sites. To overcome practical difficulties associated with efficient application of electrode array, the method utilises "Virtual Elements" and combinatorial optimization
Lower-limb biomechanical asymmetry in maximal velocity sprint running
Full text linkAsymmetry analyses have provided valuable insight into submaximal running and walking gait. Knowledge of asymmetry in sprint running is limited due to traditional unilateral methods of data collection. The aims of the study were to develop asymmetry measures that included intra-limb variability and to investigate asymmetry of sprint running in an ecologically valid environment. Asymmetry was quantified for a group of sprint runners through the development of novel multifactorial asymmetry scores. The largest kinematic asymmetry values (7%) were smaller than the corresponding kinetic values (90%). The presence of significant athlete asymmetry suggested unilateral analyses may overlook important information. Information about individual athletes’ asymmetry may also help to inform the coaching process
Computational models of upper limb movement during functional reaching tasks for application in electrical stimulation based stroke rehabilitation
No full textIntroduction: Functional electrical stimulation (FES) has been shown to be an effective approach to upper limb stroke rehabilitation, where it assists patients' arm and shoulder movement. Model-based FES controllers have recently confirmed significant potential to improve accuracy of functional reaching tasks, but they typically require a reference trajectory to track. No upper limb FES control scheme has yet embedded a computational model of the task, however this is critical to ensure the controller reinforces the intendedmovement with high accuracy. This paper derives a computational motor control model of the task which can be embedded in FES control schemes, removing the need for a predefined reference trajectory. Methods: Kinematic data were collected using a Vicon motion capture system from unimpaired (N = 14) participants while they performed two functional reaching tasks in which they: 1) pushed a light switch, and 2) closed a drawer. In each case they starting and finished the movement with their hand on their knee. Dynamic models of each patient's arm were derived using estimated mass, inertial and stiffness parameters.Each task was posed as an optimization problem with position and velocity boundary constraints, and these were solved using iterative algorithms to yield computational models of movement.Results: For the case of unimpaired participants, the experimentally recorded joint angles were compared with those derived in simulation using the model, and were found to fit closely (mean fitting > 85%).Conclusion: Functional movements have been accurately modelled as constrained optimization problems involving dynamic models of unimpaired participants' arms. This extends previous computational models of human movement, and shows that they can be solved using iterative methods. Moreover, these methods are suitable to be employed experimentally in future stroke rehabilitation trials using FES to assist task completion in a manner corresponding to unimpaired movement. This hence ensures that assistance is aligned with voluntary intention, and in-so-doing maximizes the potential effectiveness of treatment
Functional Electrical Stimulation and Iterative Learning in stroke rehabilitation for the upper limb
No full textStroke is a leading cause of disability in the UK, with approximately 50% of stroke survivors being left disabled and dependent [1]. Upper limb impairment is very common post-stroke and limits many activities of daily living, especially those requiring reach to grasp actions such as picking up a drink. Therefore, the development of rehabilitation technologies is essential to help the recovery of upper limb motor function post-stroke. Intensive, goal-orientated practice of movement is vital for recovery of upper limb function [2]. Robotic therapy and functional electrical stimulation (FES) have proved to be effective technologies in reducing upper limb impairment, enabling people with limited physical upper limb ability to practice repeated movements [2, 3]. Effectiveness of therapy is also suggested to improve when associated with the patient’s voluntary intention to move [3]. However, few rehabilitation technologies maximise voluntary effort in therapeutic interventions. This work forms part of an on-going project aimed at developing a rehabilitation system (Stimulation Assistance through Iterative Learning: SAIL) that uses robotic support and FES, mediated by advanced iterative learning control (ILC) algorithms. ILC is a technology transferred from industrial robotics. To correct performance error, after each repetition of the task, ILC uses performance data gathered from previous trials to update the FES signal that is applied during the subsequent trial. ILC encourages voluntary effort by the participant, by providing just enough FES to assist the participant in performing the movement [4]. Recent work has assessed the feasibility of ILC and FES during rehabilitation [4, 5, 6]. These studies investigated functionality following ILC controlled FES applied to the anterior deltoid and triceps during trajectory tracking tasks. Results showed that assisted and unassisted tracking performance and movement outcome scores improved over the course of 18 to 25 training sessions and that the amount of FES required to produce accurate tracking reduced [5, 6]. However, activities of daily living not only involve reaching out towards an object but also grasping and manipulating it. Our current work involves developing the SAIL technology to also stimulate muscles in the hand and wrist to facilitate functional reach to grasp tasks, such as picking up a drink. Preliminary studies to develop a biomechanical model of the arm, together with a model of human movement using motor control principles, have just finished. In these studies fourteen healthy participants, who each completed three functional tasks (turning on a light, closing a drawer and picking up a drink). Kinematic and EMG muscle activity data were collected for the upper limb. The model of the arm will be used to develop the ILC algorithms. Stroke patients will undergo rehabilitative training with the new system in Spring 2012. Clinical and biomechanical outcome measures will assess performance and identify changes in motor impairment during functional reach to grasp tasks. [1] National Audit Office Department of Health. Progress in improving stroke care. 2010. [2] Oujamaa L, Rlave I, Froger J, et al. Rehabilitation of arm function after stroke. Literature review. Annuals Physical Rehabil Med, 52: 269-293, 2009. [3] De Kroon JR, IJzerman MJ, Chae J, et al. Relation between stimulation characteristics and clinical outcome of the upper extremity in stroke. Rehabil Med, 37: 65-74, 2005. [4] Freeman, CT., et al. (2012) Iterative Learning Control in Healthcare: Electrical Stimulation and Robotic-assisted Upper Limb Stroke Rehabilitation. IEEE Control Systems Magazine. [5] Hughes AM, et al. (2009) Feasibility of iterative learning control mediated by functional electrical stimulation for reaching after stroke. Neurorehabil Neural Repair 23: 559-568. [6] Meadmore KL, et al. Iterative Learning Control mediated Function Electrical Stimulation and 3D robotics reduces motor impairment in chronic stroke. 2011, NeuroEng Rehabil. (Revision Under Review)
Implications of intra-limb variability on asymmetry analyses.
No full textThe aim of this study was to investigate the effect of intra-limb variability on the calculation of asymmetry with the purpose of informing future analyses. Asymmetry has previously been quantified for discrete kinematic and kinetic variables; however, intra-limb variability has not been routinely included in these analyses. Synchronized lower-limb kinematic and kinetic data were collected from eight trained athletes (age 22 ± 5 years, mass 74.0 ± 8.7 kg, stature 1.79 ± 0.07 m) during maximal velocity sprint running. Asymmetry was quantified using a modified version of the symmetry angle for selected kinematic and kinetic variables. Significant differences (P < 0.05) between left and right values for each variable were calculated to indicate intra-limb variability relative to between-limb differences. Significant asymmetry was present in only 39% of kinematic variables and 23% of kinetic variables analysed. Large kinetic asymmetry values (>90%) were calculated for some athletes that were not significant, due to large intra-limb variability. Variables that displayed significant asymmetry were athlete-specific. Findings highlight the potential for misleading results if intra-limb variability is not included in asymmetry analyses. The exclusion of asymmetry scores for variables not displaying significant asymmetry will be useful when calculating overall asymmetry for different participants and could be applied to future running gait analyses
Considerations of force plate transitions on centre of pressure calculation for maximal velocity sprint running
No full textThe aims of this study were to evaluate the accuracy of centre of pressure (COP) data obtained during transition of load across the boundary between two force plates, and secondly to examine the effect of such COP data on joint kinetics during sprint running performances. COP data were collected from two piezoelectric force plates as a trolley wheel was rolled across the boundary between the plates. Position data for the trolley were collected using an opto-electronic motion analysis system for comparison with COP data. Mean COP errors during transition across the plate boundary were 0.003 +/- 0.002 m relative to a control point. Kinematic and kinetic data were also collected from eight athletes during sprint running trials to demonstrate the sensitivity of the inverse dynamics analysis to COP error for the ground contact phase of the dynamic movement trials. Kinetic sensitivity to the COP error was assessed during the entire stance phase for the ankle, knee, and hip joints and was less than 5% and 3% for joint moment and power data, respectively. Based on the small COP error during transition across plate boundaries, it is recommended that foot contacts overlapping two force plates may be included in inverse dynamics analyses
Gait asymmetry: composite scores for mechanical analyses of sprint running
No full textGait asymmetry analyses are beneficial from clinical, coaching and technology perspectives. Quantifying overall athlete asymmetry would be useful in allowing comparisons between participants, or between asymmetry and other factors, such as sprint running performance. The aim of this study was to develop composite kinematic and kinetic asymmetry scores to quantify athlete asymmetry during maximal speed sprint running. Eight male sprint trained athletes (age 22±5 years, mass 74.0±8.7kg and stature 1.79±0.07m) participated in this study. Synchronised sagittal plane kinematic and kinetic data were collected via a CODA motion analysis system, synchronised to two Kistler force plates. Bilateral, lower limb data were collected during the maximal velocity phase of sprint running (velocity=9.05±0.37ms?1). Kinematic and kinetic composite asymmetry scores were developed using the previously established symmetry angle for discrete variables associated with successful sprint performance and comparisons of continuous joint power data. Unlike previous studies quantifying gait asymmetry, the scores incorporated intra-limb variability by excluding variables from the composite scores that did not display significantly larger (p<0.05) asymmetry than intra-limb variability. The variables that contributed to the composite scores and the magnitude of asymmetry observed for each measure varied on an individual participant basis. The new composite scores indicated the inter-participant differences that exist in asymmetry during sprint running and may serve to allow comparisons between overall athlete asymmetry with other important factors such as performance.<br/
Surface markers versus clusters for determining lower limb joint kinematics in sprint running
Full text linkThe purpose of this study was to compare lower limb joint angle time histories using surface markers and segmental clusters. An athlete completed three single leg standing trials whilst moving the joints of the free leg from maximum flexion to maximum extension followed by seven maximal sprint runs. Trials were tracked by a three-dimensional CODA system. For standing trials, mean timing differences were greatest in maximum extension at the ankle and hip (0.01 s). Angle differences ranged from 2° (knee flexion) to 11° (ankle extension). Timing differences in sprinting were greatest in extension (hip 0.03 s) with joint angle differences in maximum flexion and extension 7 & 9° (ankle), 3 & 6° (knee) and 23 & 4° (hip) respectively. When comparing results from surface markers and clusters, a good level of agreement was found in the continuous knee flexion-extension profile, and the discrete timings for all joints
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