Kinematic synergy in a real and a virtual simulated assembly task

In ergonomics, digital mock-ups of workstation design in virtual reality environments are often used to evaluate the occupational risks related to a working condition. However, the effectiveness of such technology, particularly in terms of human performance can be questionable. In the present study, we investigated the pattern of movement variability in a simulated assembly task and presented an index of task performance that can highlight the differences in terms of motor control strategy between a real assembly task and its virtual simulation. The movement variability was decomposed into goal-equivalent and non-goal equivalent components and the ratio of these components was introduced as an index of performance. The ratio was greater in the real than in the virtual environment. This study highlights the differences in terms of motor control strategies in real and virtual environments. Practitioner Summary: A simulated assembly task was implemented in a real and a virtual environment. A performance index in light of the motor control theory was introduced. This index could discern a lower performance in the virtual compared with the real environment. The developed approach can provide an objective index to investigate the system fidelity in virtual environments.

[1]  M.S.J. Hashmi,et al.  Virtual reality applications in manufacturing process simulation , 2004 .

[2]  Jean-Claude Sagot,et al.  Virtual reality as a support tool for ergonomic-style convergence: multidisciplinary interaction design methodology and case study , 2012, J. Virtual Real. Broadcast..

[3]  Thierry Duval,et al.  Sharing and bridging information in a collaborative virtual environment: Application to ergonomics , 2013, 2013 IEEE 4th International Conference on Cognitive Infocommunications (CogInfoCom).

[4]  Charles Pontonnier,et al.  Inverse dynamics method using optimization techniques for the estimation of muscles forces involved in the elbow motion , 2009 .

[5]  I. Kapandji The Physiology of the Joints , 1988 .

[6]  P. de Leva Adjustments to Zatsiorsky-Seluyanov's segment inertia parameters. , 1996, Journal of biomechanics.

[7]  Charles Pontonnier,et al.  Shoulder Kinematics and Spatial Pattern of Trapezius Electromyographic Activity in Real and Virtual Environments , 2015, PloS one.

[8]  Gregor Schöner,et al.  Effect of accuracy constraint on joint coordination during pointing movements , 2003, Experimental Brain Research.

[9]  Charles Pontonnier,et al.  Assessing the Ability of a VR-Based Assembly Task Simulation to Evaluate PhysicalRisk Factors , 2014, IEEE Transactions on Visualization and Computer Graphics.

[10]  Rajiv Ranganathan,et al.  Motor synergies: feedback and error compensation within and between trials , 2008, Experimental Brain Research.

[11]  Maria V. Sanchez-Vives,et al.  From presence to consciousness through virtual reality , 2005, Nature Reviews Neuroscience.

[12]  Gregor Schöner,et al.  Identifying the control structure of multijoint coordination during pistol shooting , 2000, Experimental Brain Research.

[13]  Ronald R. Mourant,et al.  Human Factors Issues in Virtual Environments: A Review of the Literature , 1998, Presence.

[14]  M. Suzuki,et al.  Trajectory formation of the center-of-mass of the arm during reaching movements , 1997, Neuroscience.

[15]  L. Carlton Processing visual feedback information for movement control. , 1981, Journal of experimental psychology. Human perception and performance.

[16]  M. Latash,et al.  Motor Control Strategies Revealed in the Structure of Motor Variability , 2002, Exercise and sport sciences reviews.

[17]  Gregor Schöner,et al.  The uncontrolled manifold concept: identifying control variables for a functional task , 1999, Experimental Brain Research.

[18]  J. Winters,et al.  Optimized Strategies for Scaling Goal-Directed Dynamic Limb Movements , 1990 .

[19]  Thierry Duval,et al.  Collaborative virtual environments for ergonomics: embedding the design engineer role in the loop , 2014, 2014 International Workshop on Collaborative Virtual Environments (3DCVE).

[20]  Thomas A. Stoffregen,et al.  On the nature and evaluation of fidelity in virtual environments: Applications, Implications, and Human Performance , 2019 .

[21]  Charles Pontonnier,et al.  Motion Analysis of the Arm Based on Functional Anatomy , 2009, 3DPH.

[22]  K. Maruyama,et al.  An analysis of spatiotemporal variability during prehension movements: effects of object size and distance , 1997, Experimental Brain Research.

[23]  Roy A. Ruddle,et al.  Virtual and Adaptive Environments: Applications, Implications, and Human Performance Issues , 2004, Presence: Teleoperators & Virtual Environments.

[24]  S. Axler Linear Algebra Done Right , 1995, Undergraduate Texts in Mathematics.

[25]  Gregor Schöner,et al.  Toward a new theory of motor synergies. , 2007, Motor control.

[26]  Mark L. Latash,et al.  Joint angle variability in 3D bimanual pointing: uncontrolled manifold analysis , 2005, Experimental Brain Research.

[27]  Gregor Schöner,et al.  Goal-equivalent joint coordination in pointing: affect of vision and arm dominance. , 2002, Motor control.

[28]  W. T. Dempster,et al.  SPACE REQUIREMENTS OF THE SEATED OPERATOR, GEOMETRICAL, KINEMATIC, AND MECHANICAL ASPECTS OF THE BODY WITH SPECIAL REFERENCE TO THE LIMBS , 1955 .