Control strategy for a hand balance

The goal of this study was to investigate the control strategy employed by gymnasts in maintaining a hand balance. It was hypothesized that a “wrist strategy” was used in which perturbations in the sagittal plane were corrected using variations in wrist flexor torque with synergistic shoulder and hip torques acting to preserve a fixed body configuration. A theoretical model of wrist strategy indicated that control could be effected using wrist torque that was a linear function of mass center displacement and velocity. Four male gymnasts executed hand balances and 2-dimensional inverse dynamics was used to determine net joint torque time histories at the wrist, shoulder, and hip joints in the sagittal plane. Wrist torque was regressed against mass center position and velocity values at progressively earlier times. It was found that all gymnasts used the wrist strategy, with time delays ranging from 160 to 240 ms. The net joint torques at the shoulder and hip joints were regressed against the torques required to maintain a fixed configuration. This fixed configuration strategy accounted for 86% of the variance in the shoulder torque and 86% of the variance in the hip torque although the actual torques exceeded the predicted torques by 7% and 30%, respectively. The estimated time delays are consistent with the use of long latency reflexes, whereas the role of vestibular and visual information in maintaining a hand balance is less certain

Colour based rigid body tracking using three-dimensional graphics models

This paper introduces the first stage of a new model-based approach to three-dimensional (3D) human movement tracking. A ‘generate-and-test’ matching procedure was adopted by matching rendered images of a 3D computer graphics model of the human body to target images of rigid body motion. The set of pixels to be compared were just those corresponding to the model of the body in the rendered images. The matching criterion to optimise model position and orientation was based on the minimisation of the RGB colour difference between generated model images and associated target images. The method was able to track synthetic image sequences of a half twisting somersault accurately with root mean square errors of less than 5 mm and 0.3° for position and orientation estimates respectively. The suitability of the proposed approach for rigid body motion tracking was supported by additional tracking experiments on video image sequences of ‘wooden cross’ trajectories. Comparisons of tracked estimates against manual digitising estimates returned relatively small rms difference values on both side somersault and twisting somersault movements. The proposed approach has the potential to track video images of a human torso using a rigid body model and hence to track articulated movements by successively adding segments to the model in a hierarchical manner

Model-based automatic tracking of articulated human movement

This study applied a vision-based tracking approach to the analysis of articulated, three-dimensional (3D) whole-body human movements. A 3D computer graphics model of the human body was constructed from ellipsoid solids and customized to two gymnasts for size and colour. The model was used in the generation of model images from multiple camera views with simulated environments based on measurements taken on each of three synchronized video cameras and the lighting sources present in the original recording environment. A hierarchical procedure was used whereby the torso was tracked initially to establish whole-body position and orientation and subsequently body segments were added successively to the model to establish body configuration. An iterative procedure was used at each stage to optimize each new set of variables using a score based on the RGB colour difference between the model images and video images at each stage. Tracking experiments were carried out on movement sequences using both synthetic and video image data. Promising qualitative results were obtained with consistent model matching in all sequences, including sequences involving whole-body rotational movements. Accurate tracking results were obtained for the synthetic image sequences. Automatic tracking results for the video images were also compared with kinematic estimates obtained via manual digitization and favourable comparisons were obtained. It is concluded that with further development this model-based approach using colour matching should provide the basis of a robust and accurate tracking system applicable to data collection for biomechanics studies

Video-based automatic tracking of three-dimensional human movement.

The collection of kinematic data is routinely required for the biomechanical analysis of human movements. Available methods for obtaining kinematic data can be categorised into (a) direct methods, which are often limited by bulky instrumentation, and (b) imagebased methods. Current image-based methods generally necessitate the use of artificial body markers to aid the identification of body parts. A model-based method for the automatic tracking of human movement without the aid of body markers was developed. The approach constructed a three-dimensional (3D) computer graphics human body model that was customised to individual subjects via incorporation of subject-specific anthropometric data and appropriate colouring of model segments. Video image sequences of human movement were collected from multiple synchronised camera views. The environment from each camera view was simulated so that computer-generated model images containing the human body model could be matched to the associated video images. The human body model configuration was optimised through iterative adaptation of the model configuration in order to minimise the RGB colour difference between the model images and video images. A number of synthetic and video movement sequences were analysed using the tracking method. Synthetic image sequences of rigid and articulated motion were tracked with good accuracy. The tracking estimates obtained from video data of aerial movements were compared to estimates obtained via established procedures to provide an indication of the accuracy of the proposed approach. Movements that were successfully tracked returned estimates with errors comparable to manual digitising estimates. More complex twisting movements were tracked but with larger errors on all variables. The robustness of the tracking system was investigated through examination of tracking results following systematic perturbations made to selected tracking parameters. On both synthetic and real data the tracking estimates were found to be relatiyely robust to perturbations in camera and lighting parameters and reduced colour contrast. It was concluded that the tracking system presents a viable method for marker-free human movement tracking without representing a final solution to the problem

Rugby Scrum - Machine Scrummaging Data

Experimental data and simulation output of a 120 kg rugby forward players scrummaging against an instrumented scrum machine.<div><br></div><div>DATA include:</div><div>-) Scaled and adjusted model</div><div>-) External loads</div><div>-) Joint angles from Inverse Kinematics (IK) performed in OpenSim 3.2</div><div>-) Joint kinetics from Inverse Dynamics (ID) performed in OpenSim 3.2</div><div>-) Residual Reduction Analysis (RRA) output performed in OpenSim 3.2</div><div><br></div

The kicking foot swing plane in rugby place kicking

This study aimed to determine the planarity of the kicking foot path in experienced rugby place kickers and to assess the effect of different data treatment methods on measured swing plane variables. Thirteen kickers completed a series of kicks and a least squares plane was fitted to the kicking foot CM trajectory throughout various lengths of the downswing using orthogonal regression. The foot path was typically planar for the last 1.25 m of the downswing. The swing planes were inclined at 50.0 ± 4.2° to the horizontal and the line of intersection between the swing planes and the global horizontal plane was directed 22.3 ± 3.5° right of target. It was proposed that swing planes should be fitted to data sampled at equal spatial divisions and that kicking foot swing planes could offer a useful context for understanding more about proximal technical factors in place kicking.</p

Mass distribution of the MASI derived from previous models and values from <i>in vitro</i> study [43].

<p>Mass distribution of the Rugby Model calculated from DEXA values of a rugby forward player (1.84 m; 120.4 Kg). Masses are reported as percentage of total body mass. The principal moment of inertia (I_XX, I_YY, I_ZZ) for the Rugby Model are shown in the las three columns of the table, and are expressed in kgm².</p

MASI

Provides the MASI (.osim) file that can be used in OpenSim.<div><br></div><div> <p>The ‘Musculoskeletal model for the Analysis of Spinal Injury’ (MASI) wascreated in OpenSim (OpenSim 3.2, Simbios, Stanford, CA, USA) and Matlab software (Matlab 2013b, MathWorks, Natick, MA, USA).</p><p>MASI inherited the structure of the OpenSim head and neck model (Vasavada Model) which we embedded into a full body model (‘2354’), and was implemented to provide, for the first time, the linkage between cervical spine, upper limb, torso and lower limbs. </p><p>MASI comprises 35 rigid anatomical segments, 78 upper and lower cervical muscles divided into 19 muscle groups, along with 23 torque actuators representing lower and upper limb muscles’ actions. Motion between body segments was permitted via 34 joints and 30 kinematic constraints. To incorporate the effect of upper limb position, a new scapula-clavicular joint (SCJ) (combining the joint motions of the acromioclavicular and sternoclavicular joints) was developed and included in the MASI, replacing the welded scapula-clavicular joint of the original head and neck model. The model had 43 degrees of freedom, though these were reduced to 37 by locking the metatarsophalangeal and wrist joints into the neutral position.</p> </div

The SCJ’s reference systems on scapula (acromionclavicular) and clavicle (sternoclavicular) joints and their coupling functions driven by humeral elevation.

<p>The sternoclavicular joint origin on the sternal extremity of the clavicle and its reference system were designed to allow depression/elevation rotation about the x-axis, protraction/retraction rotations about the y-axis, and axial rotation about the z-axis. The motion of this joint is driven by the humeral elevation via 3 coordinate-coupler constraints based on spline functions. The acromionclavicular joint was designed with a glenoid-based reference system which allows lateral/medial rotation on x-axis, protraction/retraction rotations on y-axis, and anterior-posterior tilt on z-axis. The glenoid based system had the z-axis perpendicular to the glenoid plane, the y-axis directed superiorly toward the superior glenoid tubercle, and the x-axis directed anteriorly perpendicular to the other 2 axes. The motion of the acromionclavicular joint is driven by the sternoclavicular joint motion via 3 coordinate-coupler constraints based on linear functions.</p

Rugby Model simulated neck muscle activation.

<p>Simulated muscle activation from computed muscle control (solid black line) and experimental EMG (dashed black line) of sternocleidomastoid (left column) and upper trapezius (right column) muscles during flexion, extension, lateral bending (right and left bending) and axial rotation (right and left rotation). Experimental EMG signal were normalized using maximum voluntary contraction data and defined between 0% and 100%. Simulated activations are defined between 0% (no activation) and 100% (full activation).</p