1. Computational Models to Simulate the Muscle’s Dynamics 2008/09 Introdução à Engenharia Biomédica IST/FMUL – MEBiom 1º ano / 1º semestre

2. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Introduction The Muscle - Types of muscles; - Anatomy and Physiology. Mathematical Models - Hill’s Model; - Other models. Muscle Redundancy problem - Definition - How to solve it. - An optimization problem - Optimization Criteria Applications of Muscle Modeling Future Directions Conclusion

3. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Importance of Musculoskeletal system Improvement of movement Analyzing the muscle to develop better applications and improve impaired people’s quality of life

4. Produce force Cause motion Maintain the normal body-temperature Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

5. Smooth muscle Cardiac muscle Skeletal muscle Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

6. CharacteristicsSkeletal Types of muscle Smooth Cardiac Location Disposed over the skeletal system Walls of hollow organsHeart Cell-shape Very long and cylindrical Fusiform Cylindrical and branched Function Body movement Regulation of the blood vessels’ diameter, the size of the eye pupil,… Pumping blood Control ConsciousInconscious Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

7. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

8. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

9. Multiple Fiber simulation Wave summation Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

10. Invasive Procedures Non-invasive Procedures Models: - Social Sciences; - Natural Sciences; - Engineering Problems To study Muscle Dynamics… Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Buckle-gage Transducer EMG Indeep and EMG Electrods Mathematical muscle model

11. Muscle Dynamics Models By HuxleyBy ZahalakBy HatzeBy Zajac By Hill By Chapman and Baildon Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

12. 192219241927193819391949 Frog’s sartorius muscle experiments - The Heat Production Contributions for Computational Modeling Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Archibald V. Hill

13. 192219241927193819391949 Contributions for Computational Modeling The parity between muscle and a spring-like structure working in a linearly viscous manner Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Archibald V. Hill

14. 192219241927193819391949 Contributions for Computational Modeling Model of a damped spring-like property in series with an undamped string Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Archibald V. Hill

15. 192219241927193819391949 Contributions for Computational Modeling Hill’s Model Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Archibald V. Hill

16. 192219241927193819391949 Contributions for Computational Modeling The CE in series and in parallel with passive, lightly- damped elastic tissue was understood. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Archibald V. Hill

17. 192219241927193819391949 Contributions for Computational Modeling Hill’s explicit definition and technique for estimating excitation-activation dynamics Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Archibald V. Hill

18. Hill’s Model Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

19. Hill’s Model Force-Length Relationship (a)Force-Velocity Relationship (b) Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

20. Hill’s Model Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

21. Hill’s Model Advantages The better balance between simplicity and fidelity Can easily be put in practice Obtained using measurements obtained in experiments on muscles Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

22. Hill’s Model Disadvantages The analogy to a viscoelastic system The restrictions of the model Some concepts exclusively created to the model Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

23. Muscle Redundancy problem – More Muscles than the ones needed In the body – Central Nervous System Muscle Models – Attempts to distribute the equations by the different forces generated Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

24. Reduction Methods – Reduction of the number of unknown forces until reaching the number of equations – The contribution of some structures is ignored – Functional and Anatomical assumptions – Prediction of Forces Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

25. Optimization Methods – Several Criteria – Solution that minimize the selected criterion – Fulfill with the system’s Equations of Movement Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

26. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Constrains – Equations of Movement – Muscle Length and Force production Limits

27. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Polynomial Sums Soft Saturation Min/Max Criterion Maximum Endurance Pseudoinverse Algorithm

28. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Analysis of human locomotion and muscle pathologies Ergonomics Man-Machine Interface

29. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Simulations using muscle models Studies of physical limitations, muscle pathologies and movement optimization Applications in sports Applications in the medical field

30. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso To optimize ergonomic design the human body needs to be taken into consideration Modeling the musculoskeletal system provides a major insight into the working conditions of the human body Muscle modeling’s analytical approach is complementary to empirical investigations Comfort Health and safety Goals : and It may revolutionize ergonomic design!

31. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Example of this modeling application in a seated human: Biomechanical analysis of numerous parameters

32. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Studied to support investigations in robotics Integration between a human and a robotic machine Biomedical, industrial and aerospace applications Decision making and specialized sensing mechanisms Power, accuracy and speed

33. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Example: Exoskeleton Machines Powered mobile machines Power supply that supplies at least part of the activation-energy for limb movement Human control of the task Mobility assistance to the users (prosthetics and orthotics) Powered Prosthetic Active Ortho

34. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Bring together different researchers, as this is an interdisciplinary area Collect more experimental data to ensure the veracity of muscle modeling Increase the efficiency of the present models, correcting the problems in Hill’s model in a balanced way

35. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso Mathematical models are a very useful and completely non-invasive technique to study the muscle’s dynamics This area has seen a fast growth, and several models have been proposed to model the musculoskeletal system Considering all the aspects that have to be taken in mind in muscle modeling, Hill’s Model continues to be the key model to perform these studies It is reasonable to assume that new and more efficient muscular models will be proposed in a short term period of time…

36. Prof. Miguel Tavares da Silva, Departamento de Mecânica, IST Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso

37. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso [1] B.J.J.J van der Linden, “Mechanical modelling of skeletal muscle functioning”, PhD thesis, University of Twente, Nederland,1998. [2] United States Federal Government, “Illu muscle tissues”, http://training.seer.cancer.gov/module_anatomy/images/illu_muscle_tissues.jpg, 2008. [3] Rod R.Seeley, Trent D.Stephens, Philip Tate, Anatomia e Fisiologia, 3rd edition, Lusodidátiga, 1997. [4] Visual dicionary, “Muscles”, http://www.infovisual.info/03/pano_en.html, 2008. [5] Davin, “Agonist en antagonist”, http://upload.wikimedia.org/wikipedia/commons/e/e7/Agonist_en_antagonist.jpg, 2008. [6] United States Federal Government, “Illu muscle structure”, http://training.seer.cancer.gov/module_anatomy/images/illu_muscle_structure.jpg, 2008. [7] Geralyn M. Caplan, “Muscle Structure”, www.octc.kctcs.edu/gcaplan/anat/images/Image286.gif, 2008. [8] The McGraw-Hill Companies, “Muscle Cell Function”, http://www.mhhe.com/biosci/esp/2001_gbio/folder_structure/an/m5/s5/assets/images/anm5s5_1.jpg, 2008. [9] Department of Integrative Physiology – University of Colorado, “Role of Action Potencial and Ca++ in Muscle Contraction”, http://www.colorado.edu/intphys/Class/IPHY3730/image/figure9- 2.jpg, Last Updated: May 20, 2008. [10] R. Allen and J. Grisnik, “M Line Apearence in Developing Striated Muscle”, Development Genes and Evolution Vol 167 (3), 291-293, 1971.

38. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso [11] Miguel T. Silva, “Human Motion Analysis Using Multibody Dynamics and Optimization Tools”, http://www2.dem.ist.utl.pt/~mpsilva/PhD_Thesis/Miguel_Silva_PHD_THESIS_2003.pdf, 2008. [12] Jay Todd, “Structure of Actin and Myosin”, http://academic.wsc.edu/faculty/jatodd1/351/actin_myosin.jpg, Last updated Spring 2006. [13] Jay Todd, “Neuromusclurar Junction”, http://academic.wsc.edu/faculty/jatodd1/ap1/neuromuscularjunction.jpg, Last updated 2006. [14] Nobel Foundation, “Archibald Hill”, http://nobelprize.org/nobel_prizes/medicine/laureates/1922/hillbio.html”, 2008. [15] Zajac, Felix E.,“Muscle and Tendon:Properties,Models,Scaling and application to biomechanics and motor control”, CRC Critical Reviews in Biomedical Engineering, Boca Raton, CRC Press, Vol.17, 1989. [16] Hill, Archibald V., “A note on the elasticity of skeletal muscles”, J. Physiol in jp.physoc.org, 2008. [17] G. K. Cole, A. J. van den Bogert, W. Herzog, K. G. M. Gerritsen, “Muscle coordination of movement: a perspective”, Journal of Biomechanics, Vol 29(8), 1091-1104, August 1996. [18] F. E. Zajac, “Muscle coordination of movement: a perspective”, Journal of Biomechanics, Vol 26(1), 109- 124, 1993. [19] F.E. Zajac, E.L. Topp, P.J. Stevenson, A dimensionless musculotendon model, in: Proc. 8th Conf. IEEEEng. Med. Biol. Soc., 601–604, 1986. [20] F.E. Zajac, E.L. Topp, P.J. Stevenson, Musculotendon actuator models for use in computer studies and design of neuromuscular stimulation systems, Proc. 9th A. Conf. Rehabil. Tech. (RESNA), 442–444, 1986.

39. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso [21] Hatze, Herbert, “Neuromusculoskeletal Control Systems Modeling – A Critical Survey of Recent Developments”, Transactions on Automatic Control, Vol. 25(3), 1980. [22] K. R. Kaufman, M.S., K. N. An, Ph.D. and E. Y. S. Chao, Ph.D.,”Length-Tension Relationship and muscle force determination”, Advances on Bioengineering, Vols. 3 and 12, 53-54, 1987. [23] M. L. Audu and D. T. Davy, “The influence of Muscle Model Complexity in Musculoskeletal Motion Modeling”, Journal of Biomechanical Engineering, Vol. 107/147, 147-157, 1985. [24] Freivads, Andris, “Mechanics, Modeling, and Musculoskeletal Injuries”, CRC Press, 138-149, 2004. [25] R. W. A. Baildon and A. E. Chapman, “A new approach to the human muscle model”, Journal of Biomechanics, Vol 16(10), 803-809, 1983. [26] Erik Forster, “Predicting Muscle Forces in the Human Lower Limb during Locomotion”, http://vts.uniulm. de/docs/2004/3722/vts_3722.pdf, December 2008. [27] Erik Forster et all, “Predicting Muscle Forces in the Human Lower Limb during Locomotion” – powerpoint presentation, http://www.mathematik.uni-ulm.de/numerik/wissrech/26092003/forster.pdf, December 2008. [28] Crowninshield RD, Brand RA. “A physiologically based criterion of muscle force prediction in locomotion”, Journal of Biomechanics, Vol. 14(11), 793-801, 1981. [29] G. T. Yamaguchi, D. W. Morgan and J. Sit, “A Computationally efficient method for solving the Redundant Problem in Biomechanics”, Journal of Biomechanics, Vol. 28(8), 999-1005, 1995. [30] “Qualysis Motion Capture Systems’ Applications and Application Notes”, http://www.qualisys.com/default.asp?viewset=1&on=%27Applications%27&id=&initid=49&heading =Applications&mainpage=templates/Q02.asp?sida=41, 2008.

40. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso [31] J. Rasmussen, et al., “Musculoskeletal Modeling As An Ergonomic Design Method”, The AnyBody Group, Institute of Mechanical Engineering, Allborg University, Denmark, 2008. [32] Rosen J., M. B. Fuchs, and M. Arcan, “Performances of Hill-Type and Neural Network Muscle Models - Towards a Myosignal Based Exoskeleton”, Computers and Biom. Research, Vol. 32 (5), 415-439, 1999. [33] “Powered exoskeleton”, http://en.wikipedia.org/wiki/Powered_exoskeleton, December 8, 2008. [34] Olympica Internacional, “Ortroses no Desporto”, http://alternet.pt/olympica/teleolympica/ ortoteses.html, December 10, 2008. [35] Nobel Foundation, “Archibald Hill”, http://nobelprize.org/nobel_prizes/medicine/laureates/1922/hillbio. html”, 2008. [36] Hill, Archibald V., “A note on the elasticity of skeletal muscles”, J. Physiol in jp.physoc.org, 2008. [37] F. E. Zajac, “Muscle coordination of movement: a perspective”, Journal of Biomechanics, Vol 26(1), 109-124, 1993. [38] Crowninshield RD, Brand RA. “A physiologically based criterion of muscle force prediction in locomotion”, Journal of Biomechanics, Vol. 14(11), 793-801, 1981. [39] Thomas M. Nosek, “Vertebrate Neuromuscular Junction: Release of Acetylcholine”, http://www.lib.mcg.edu/edu/eshuphysio/program/section2/2ch1/2ch1img/neuromus.jpg, 2008. [40] Hill, Archibald V., "The Mechanism of Muscular Contraction“, http://nobelprize.org/nobel_prizes/medicine/laureates/1922/hill-lecture.html, 2008. [41] Audu, Musa L. and Davy, Dwight T., “A comparison fo different muscle models in human motion studies”, Advances in Bioengineering, ASUE, 1984.

41. Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso [42] “Computer Simulation”, http://en.wikipedia.org/wiki/Computer_simulation, Last updated: December 7, 2008=templates/Q02.asp?sida=41, 2008. [43] Collins, S.H., Wisse, M., Ruina, A., “A 3-D Passive Dynamic Walking Robot with Two Legs and Knees, International Journal of Robotics Research”, The International Journal of Robotics Research, Vol. 20 (7), 607-615, 2001. [44] Tedrake, R., Zhand, T.W., Fong, M.F., Seung, H.S., “Actuating a Simple 3D Passive Dynamic Walker”, Proc. IEEE Int. Conf. Robotics & Automation, New Orleans, LA: 4656-4661, 2004. [45] “Passive Walking”, http://wwwpersonal.umich.edu/~artkuo/Passive_Walk/passive_walking.html, 2008. [46] Steve Collins, “Walking Robots”, http://wwwpersonal.umich.edu/~shc/robots.html, 2008. [47] Kumar, Shrawan, “Biomechanics in Ergonomics”, CRC Press, Inc., Second Edition, 2007. [48] Zahalak, George I. Multiple Muscle Systems: Biomechanics and Movement Organization, Springer- Verlag, New York, 1990. [49] Rasmussen,J., Damsgaard,M., and Voigt,M., “Muscle recruitment by the min/max criterion - a comparative numerical study”, Journal of Biomechanics, Vol. 34, 409-415, 2001. [50] Collins J.J., “The redundant nature of locomotor optimization laws”, Journal of Biomechanics, Vol. 28 (3), 1995. [51] - "Prosthethic Enhancements", http://en.wikipedia.org/wiki/File:Oscar_Pistorius-2.jpg [52] - "Powered Prosthethic", http://img.timeinc.net/popsci/images/2006/06/prosthbook_ss_2.jpg [53] - "AnyBody Modeling System in Aerospace", http://www.nexgenergo.com/ergonomics/anybodyapp1.html

42. Obrigado pela vossa atenção! Computational Models to Simulate the Muscle’s Dynamics Jonathan Ribeiro / Pedro Chagas Pedro Pinheiro / Pedro Afonso