Characterization of the shoulder net joint moment during manual wheelchair propulsion using four functional axes.

Understanding how individuals distribute mechanical demand imposed on their upper extremity during physically demanding activities provides meaningful insights to preserve function and mitigate detrimental mechanical loading of the shoulder. In this study, we hypothesized that parameterization of the shoulder net joint moment using four functional axes could characterize distribution tendencies about the shoulder during manual wheelchair propulsion and that regardless of demographics, a shoulder flexor dominant NJM distribution would be predominantly used by individuals with paraplegia (n = 130). Forces and kinematics of the upper extremity and trunk were quantified using motion capture and an instrumented wheel during steady state manual wheelchair propulsion at self-selected fast speeds on a stationary ergometer. The results indicate that parsing out the internal/external rotation component of the shoulder net joint moment about the upper arm and distributing the remainder across the three orthogonal axes of the torso was successful in identifying common shoulder net joint moment distribution techniques used across individuals with paraplegia during manual wheelchair propulsion. Distribution tendencies were predominantly flexor dominant across injury level, gender, time since injury, body mass index, and height demographics. The 4-axis parameterization of the shoulder NJM effectively differentiated moment distribution tendencies used by individuals during manual wheelchair propulsion using a functionally relevant representation of shoulder kinetics. Use of the four-axis parameterization of joint kinetics in future studies is expected to provide important insights that can advance knowledge, preserve function, and inform clinical decisions.

Regulation of reaction forces during the golf swing.

During the golf swing, the reaction forces applied at the feet control translation and rotation of the body-club system. In this study, we hypothesized that skilled players using a 6-iron would regulate shot distance by scaling the magnitude of the resultant horizontal reaction force applied to the each foot with minimal modifications in force direction. Skilled players (n = 12) hit golf balls using a 6-iron. Shot distance was varied by hitting the ball as they would normally and when reducing shot distance using the same club. During each swing, reaction forces were measured using dual force plates (1200 Hz) and three-dimensional kinematics were simultaneously captured (110 Hz). The results indicate that, on average, the peak resultant horizontal reaction forces of the target leg were significantly less than normal (5%, p < 0.05) when reducing shot distance. No significant differences in the orientation of the peak resultant horizontal reaction forces were observed. Resultant horizontal reaction force-angle relationships within leg and temporal relationships between target and rear legs during the swing were consistent within player across shot conditions. Regulation of force magnitude with minimal modification in force direction is expected to provide advantages from muscle activation, coordination, and performance points of view.

Parameter optimization model of learning in stepping motion.

In this study we combine the representation of motion by a finite number of hardwired functions with parameter optimization to model learning during a stepping motion. Representation of experimental kinematic data by a finite number of predetermined functions and undetermined coefficients was analyzed. Least squares approximation was used to represent experimental data of stepping motions over obstacles of different heights. Functional relationships between coefficients and obstacles heights were also obtained. Learning of stepping over an obstacle was then formulated as a finite dimensional optimization problem. The pattern of foot path, and joint angles trajectories obtained by this learning model, were then compared to the experimental data. The results of the data fitting analysis and of the optimization process as a model for motion learning, indicate that motion can be adequately represented by a set of hardwired functions, and a finite number of task dependent coefficients.

Fitting mathematical functions to joint kinematics during stepping: implications for motor control.

The present study extends past work on modeling and control of stepping. The relationship between joint space kinematic data and routine motor control (i.e., open loop) during human stepping is investigated. A model of open loop stepping control using joint kinematics is described. Different functional approximations are employed to simulate experimental joint kinematic data collected on a subject stepping repeatedly over an obstacle. Results indicate that joint kinematics can be characterized by a small number of functions yielding a simple analytical description of open loop motor control. The different basis functions used and their associated coefficients reflected the qualitative behavior of joint trajectories thus allowing flexibility in the formulation of system kinematics. This approach provides a tool to study movement pathologies and movement development by identifying the basis functions governing the kinematics of motion and their associated coefficients. The model presented here is helpful in studying the segmentation of multiarticular movements into their elementary components by analytically modeling the discrete organization of motor behavior.

Modeling of control and learning in a stepping motion.

In a previous study (Beuter et al. 1986) the authors modeled a stepping motion using a three-body linkage with four degrees of freedom. Stepping was simulated by using three task parameters (i.e., step height, length, and duration) and sinusoidal joint angular velocity profiles. The results supported the concept of a hierarchical control structure with open-loop control during normal operation. In this study we refine the dynamic model and improve the simulation technique by incorporating the dynamics of the leg after landing, adding a foot segment to the model, and preprogramming the complete step motion using cycloids. The equations of the forces and torques developed on the ground by the foot during the landing phase are derived using the Lagrangian method. Simulation results are compared to experimental data collected on a subject stepping four times over an obstacle using a Selspot motion analysis system. A hierarchical control model that incorporates a learning process is proposed. The model allows an efficient combination of open and closed loop control strategies and involves hardwired movement segments. We also test the hypothesis of cycloidal velocity profiles in the joint programs against experimental data using a novel curve-fitting procedure based on analytical rather than numerical differentiation. The results suggest multiobjective optimization of the joint's motion. The control and learning model proposed here will help the understanding of the mechanisms responsible for assembling selected movement segments into goal-directed movement sequences in humans.

Phase plane modeling of leg motion.

Phase plane analysis of dynamical systems, in which variables are plotted against their time derivatives, has been recently emphasized as a general method for reconstructing system dynamics from data. The purpose of this experiment was to develop a model of leg movement in a stepping task using the phase plane approach. In this model, the leg is represented as a three-body linkage and the motion of the leg is assumed to be planar with four degrees of freedom. Experimental data was collected on one subject stepping six times, using a two dimensional videomotion analysis system with reflective markers placed on the lower limb joints. A computer program able to solve the equations of motion and compute the state of the system for a given task was implemented. This computer program was written to generate the motion of the leg for a given task using inverse kinematics and a preplanned foot path. Foot trajectories with cycloidal, constant acceleration/deceleration and sinusoidal velocity profiles were studied. From the results, an attempt was made to identify the variables which are measured and to determine the motion characteristics during stepping. The preliminary results support the concept of a hierarchical control structure with open-loop control during normal operation. During routine activity there is no direct intervention of the Central Nervous System (CNS). The results support the existence of preprogramming and provide a starting point for the study of the development of control in multiarticulate movements.