Optimizing the actuation of musculoskeletal model by genetic algorithm to simulate the vertical jump

Document Type : Persian

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Abstract

In human body movement simulation such as vertical jump by a forward dynamic model, optimal control theories must be used. In the recent years, new methods were created for solving optimization problems which they were adopted from animal behaviors and environment events such as Genetic algorithm, Particle swarm and Imperialism competitive. In this work, the skeletal model was constructed by Newton-Euler equation of motion. This 2D model has 4 rigid segments that include foot, shank, thigh and HAT (Head, Arm and Trunk) and all joints were assumed to be revolute and ideal. Also 20 effective muscles in vertical jump were constructed as joint actuator. The ground reaction force was simulated by a spring-damper element. Additionally, joints ligament were constructed to simulate the joint out of range motion. The Genetic algorithm was used to generate the best muscle excitation for maximum height in vertical jumping and the generated muscles excitations were converted to muscles activations. The muscles activations were applied to muscles model to generate muscles force. The maximum height of jump was considered as a criteria function of optimization problem. The designed genetic algorithm could control the musculoskeletal and simulate the vertical jump movement. The result showed that the height of center of mass was equal to 121.67 cm after 533 iterations. It is looks to be able to obtain better result provided to increase the iteration or combining clever algorithms together.

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References

[1] Reinbolt J.A., Seth A., Delp S.L., Simulation of human movement: applications using OpenSim, IUTAM Symposium on Human Body Dynamics, Waterloo, 2011,  pp.186-198.
[2] Millard M., Uchida T., Seth A., Delp S.L., Flexing computational muscle: Modeling and simulation of musculotendon dynamics, Journal of Biomechanical Engineering, Vol. 135(2), 2013, 021004 (11 pages).
[3] Pandy M., Anderson F.C., Hull D., A parameter optimization approach for the optimal control of large-scale musculoskeletal systems, Journal of Biomechanical Engineering, Vol. 114(4), 1992,  pp. 450.
[4] Thelen D.G., Anderson F.C., Using computed muscle control to generate forward dynamic simulations of human walking from experimental data, Journal of biomechanics, Vol. 39(6), 2006, pp. 1107.
[5] Gündoğdu Ö., Anderson K.S., Parnianpour M., Development of a genetic algorithm based biomechanical simulation of sagittal lifting tasks, Biomedical Engineering: Applications, Basis and Communications, Vol. 17(01), 2005, pp. 12-18.
[6] Lenjan nejadian Sh., Rostami M., Genetic algorithm optimization applied to a biomechanical model of snatch lift, International Journal of Computer Science in Sport, Vol.  9(1), 2010.
[7] Cheng K.B., Wang C.H., Chen H.C., Wu C.D., Chiu H.T., The mechanisms that enable arm motion to enhance vertical jump performance –A simulation study, Journal of biomechanics, Vol. 41(9), 2008, pp. 1847-1854.
 [8] Ashby B.M., Delp S.L., Optimal control simulations reveal mechanisms by which arm movement improves standing long jump performance. Journal of biomechanics, Vol. 39(9), 2006,  pp. 1726-1734.
 [9] Anderson F.C., Pandy M.G. A dynamic optimization solution for vertical jumping in three dimensions, Computer Methods in Biomechanics and Biomedical Engineering, Vol. 2(3), 1999, pp. 201-231.
[10] Chaffin D.B., Andersson G., Bernard J. M., Occupational biomechanics, Wiley, 1991.
[11] Audu, M.L., Optimal control modeling of lower extremity musculoskeletal motion, Ph.D. Dissertation, Case Western Reserve University, 1985.
[12] Pandy M.G., Zajac F.E., Sim E., William S.L., An optimal control model for maximum-height human jumping, Journal of biomechanics, Vol. 23(12), 1990, pp. 1185-1198.
[13] Zajac F.E., Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Critical reviews in biomedical engineering, Vol. 17(4), 1989, pp. 359.
[14] Delp S.L., Loan J.P., Hoy M.G., Zajac F.E., Topp E.L., Rosen J.M., An interactive graphics-based model of the lower extremity to study orthopedic surgical procedures, Biomedical Engineering, IEEE Transactions on, Vol. 37, 8, 1990, pp. 757-767.
[15] Anderson F.C., A dynamic optimization solution for a complete cycle of normal gait, Ph.D. Dissertation, University of Texas at Austin, 1999.
[16] Thelen, D.G., Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults. Journal of biomechanical engineering, Vol. 125(1), 2003, pp. 70-77.
 
 

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