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A Biomechanical Model for Evaluation of Shoulder Function: Detecting the
Relationship Between Muscles Activation Patterns and Shoulder Joint Torques Using Synergy Concept

Nassajian Moghadam, Mohamad Reza | 2010

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 40310 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Parnianpour, Mohamad; Asghari, Mohsen
  7. Abstract:
  8. The effects of combined task demands on the way muscles are recruited to balance external loads during posture and movement is of great importance in quantitative analysis of upper arm function. Pain and disability of shoulder joint is becoming more important as population spends more often interacting with computers in seated position and carrying repetitive tasks using upper extremities. Shoulder joint that is more dependent on the muscles for its normal function than other joints such as hip due to its small articular surface and large range motion has been used here to study its coordination during isometric exertions. Since, the numbers of tasks that could be performed are enormous. In shoulder disease, a large variety of evaluation tools is employed to assess the function of shoulder. However, even if the majority of these evaluations are largely widespread, none was accepted as a universal standard. Since 1990, some researchers have been evaluating the assumption that the movement analysis is likely to provide objective results. To quantify shoulder performance in order to evaluate shoulder function, we need to determine the biomechanical performance parameters involved in shoulder tasks such as kinematic and dynamic demands of the task. We have direct measurement of some of task demands such as joint kinematics and muscle activities via some ambulatory devices and EMG recording devices during daily shoulder activities outside the laboratory. However, the other task demands such as the required torques need computational models using the external loads and the measurements of joint kinematics with respect to an inertial frame of reference. The estimation of shoulder torque is a good example that cannot be adequately estimated by joint kinematics alone, since the external loads (i.e. hand forces) must be characterized as well. Many technologies have become available to sense the limb position in space and are suggested for future risk assessment or ergonomic workplace evaluation. Fusion of these devices with EMG activities to estimate the joint external moment is a key research goal of this study. Managing the problem to balance kinematic or dynamics of the system requires controlling a large number of variables in muscles and joints across all limbs and is difficult due to the variety, complexity and range of upper arm movements. Therefore effective and robust techniques are needed to reduce the dimensionality in data and to extract useful information from quantitative variables. Recently, it’s showed that, the central nervous system (CNS) manages the high dimensionality existed in the control of multiple muscles in human movement or isometric attempts, by generating a few fundamental controlling signals known as synergies where each synergy is defined as a set of muscles recruited by a single neural command signal. It reduces the dimensionality, yet allows flexibility in the final expression of muscle activation. In this study we have utilized synergy concept as a CNS simplifying strategy for the control of the system, to present a method to see how muscle synergy recruitment address a specific joint torque during a special shoulder task, we have used an numerical optimization base shoulder model to obtain muscle activation levels, when an external isometric torque exerted at shoulder glenohumeral joint, varies in two dimensional plane of flexion/extension and abduction/adduction moment space while shoulder is kept at a spatial given position isometrically. In our validated 3D biomechanical shoulder model, we have used an optimization approach to solve the redundancy problem: minimizing the maximum muscle force while subjecting the muscles to balancing the external moments (3D equilibrium conditions are satisfied) and keeping the muscles bounded between zero and maximum muscle force assigned based on each of their physiological cross sectional area to extract muscle activation level in each simulated task. Using extracted muscle activation data we have utilized Nonnegative Matrix Factorization as a method for grouping muscles in some fixed element synergies, since muscle forces are always positive and we cannot allow muscle synergies to have negative muscle forces. Then we have scrutinized how recruiting muscle synergies lead to a specific torque direction at shoulder. In this way, we provide a relationship between a specific group of muscles recruited in a synergy and produced torque direction at shoulder. This study determined that by a few numbers synergies we can reconstruct the external torque and muscular activation of muscles with great deal of accuracy. Each of the emerging synergy had a number of muscles contributing to it and a muscle was member of more than one synergy. This approach captures the internal coordinative structure of the redundant system and provides an opportunity to compare the experimental and theoretical recruitment patterns to evaluate the biomechanical, neural and control aspects of muscular control. The advantage of using numerical simulations is that the muscle activations obtained here are not suffering from the various cross-talk problems and nonlinearities we encounter during experimental approaches.

  9. Keywords:
  10. Shoulders Joint ; Synergy ; Muscle Activation Level ; Anybody Software

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