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Development of a revolute-type kinematic model for human upper limb using a matrix approach

Published online by Cambridge University Press:  27 September 2021

Anil Kumar Gillawat*
Affiliation:
Mechanical Engineering Department, National Institute of Technology Calicut, Kerala, India E-mail: anilkumargillawat@gmail.com

Abstract

A mathematical model is proposed for a revolute joint mechanism with an n-degree of freedom (DOF). The matrix approach is used for finding the relation between two consecutive links to determine desired link parameters such as position, velocity and acceleration using the forward kinematic approach. The matrix approach was confirmed for a proposed 10 DOF revolute type (R-type) human upper limb model with servo motors at each joint. Two DOFs are considered each at shoulder, elbow and wrist joint, followed by four DOF for the fingers. Two DOFs were considered for metacarpophalangeal (mcp) and one DOF each for proximal interphalangeal (pip) and distal interphalangeal (dip) joints. MATLAB script function was used to evaluate the mathematical model for determining kinematic parameters for all the proposed human upper limb model joints. The simplified method for kinematic analysis proposed in this paper will further simplify the dynamic modeling of any mechanism for determining joint torques and hence, easy to design control system for joint movements.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Disability and Health [Internet], WHO. (2020) [cited 2021 Jul 13]. pp. 1–1. Available from: https://www.who.int/news-room/fact-sheets/detail/disability-and-health Google Scholar
Cordella, F., Ciancio, A. L., Sacchetti, R., Davalli, A., Cutti, A. G., Guglielmelli, E. and Zollo, L., “Literature review on needs of upper limb prosthesis users,” Front. Neurosci. 10, 114 (2016). https://doi.org/10.3389/fnins.2016.00209 CrossRefGoogle ScholarPubMed
Slavens, B. A. and Harris, G. F., “The biomechanics of upper extremity kinematic and kinetic modeling: applications to rehabilitation engineering,” Crit. Rev. Biomed. Eng. Begell House Inc.; 36, 93125 (2008). https://doi.org/10.1615/critrevbiomedeng.v36.i2-3.20 CrossRefGoogle Scholar
Maciejasz, P., Eschweiler, J., Gerlach-Hahn, K., Jansen-Troy, A. and Leonhardt, S., “A survey on robotic devices for upper limb rehabilitation,” J. NeuroEng. Rehabil. 11(3), 129 (2014). https://doi.org/10.1186/1743-0003-11-3 CrossRefGoogle ScholarPubMed
Kandori, A., Miyashita, T., Hosono, N., Yokoe, M., Ogata, K., Abe, K. and Sakoda, S., “Motion analysis of grip and release with fingers using simple magnetic detection system,” Rev. Sci. Instrum. 78, 034302, 16 (2007). https://doi.org/10.1063/1.2712915 CrossRefGoogle ScholarPubMed
Derrick, T. R., van den Bogert, A. J., Cereatti, A., Dumas, R., Fantozzi, S. and Leardini, A., “ISB recommendations on the reporting of intersegmental forces and moments during human motion analysis,” J. Biomech. 99, 109533, 133 (2020). https://doi.org/10.1016/j.jbiomech.2019.109533 CrossRefGoogle ScholarPubMed
Mesquita, I. A., da Fonseca, P. F. P., Pinheiro, A. R. V., Velhote Correia, M. F. P. and da Silva, C. I. C., “Methodological considerations for kinematic analysis of upper limbs in healthy and poststroke adults Part II: a systematic review of motion capture systems and kinematic metrics,” Top. Stroke Rehabil. 26(6), 464472 (2019). https://doi.org/10.1080/10749357.2019.1611221 CrossRefGoogle ScholarPubMed
Ozawa, R., Kobayashi, H. and Hashirii, K., “Analysis, classification, and design of tendon-driven mechanisms,” IEEE Trans. Rob. 30(2), 396410 (2014). https://doi.org/10.1109/TRO.2013.2287976 CrossRefGoogle Scholar
Armstrong, T. J. and Chaffin, D. B., “An investigation of the relationship between displacements of the finger and wrist joints and the extrinsic finger flexor tendons,” J. Biomech. 11(3), 119128 (1978). https://doi.org/10.1016/0021-9290(78)90004-0 CrossRefGoogle ScholarPubMed
Lee, K. H., Baek, S. G., Lee, H. J., Choi, H. R., Moon, H. and Koo, J. C., “Enhanced transparency for physical human-robot interaction using human hand impedance compensation,” IEEE/ASME Trans. Mechatron. 23(6), 26622670 (2018). https://doi.org/10.1109/TMECH.2018.2875690 CrossRefGoogle Scholar
Jiang, X., Xiong, C., Sun, R. and Xiong, Y., “Characteristics of the robotic arm of a 9-DoF upper limb rehabilitation robot powered by pneumatic muscles,” In: Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science (H. Liu, H. Ding, Z. Xiong and X. Zhu, eds.), vol. 6425 (Springer, Berlin, Heidelberg, 2010) pp. 463474. https://doi.org/10.1007/978-3-642-16587-0_43 Google Scholar
Kuhn, J., Ringwald, J., Schappler, M., Johannsmeier, L. and Haddadin, S., “Towards semi-autonomous and soft-robotics enabled upper-limb exoprosthetics: first concepts and robot-based emulation prototype,” In: IEEE International Conference on Robotics and Automation (ICRA) (A. Howard and A. Okamura, eds.) (2019) pp. 91809186. https://doi.org/10.1109/ICRA.2019.8794332 CrossRefGoogle Scholar
Ang, B. W. K. and Yeow, C. H., “Design and characterization of a 3d printed soft robotic wrist sleeve with 2 DoF for stroke rehabilitation,” 2nd IEEE International Conference on Soft Robotics (RoboSoft) (2019) pp. 577582. https://doi.org/10.1109/ROBOSOFT.2019.8722771 CrossRefGoogle Scholar
Majidi Fard Vatan, H., Nefti-Meziani, S., Davis, S., Saffari, Z. and El-Hussieny, H., “A review: a comprehensive review of soft and Rigid wearable rehabilitation and assistive devices with a focus on the shoulder joint,” J. Intell. Robot Syst. 102(9), 124 (2021). https://doi.org/10.1007/s10846-021-01353-x CrossRefGoogle Scholar
Pandey, R. and Mandal, M., “Robotic Intervention for Elderly – A Rehabilitation Aid for Better Living,” In: Intelligent Human Computer Interaction. 11th International Conference, IHCI 2019, Allahabad, India, December 12–14, 2019. Lecture Notes in Computer Science (U. Tiwary and S. Chaudhury, eds.), vol. 11886 (Springer, Cham, 2020) pp. 203211. https://doi.org/10.1007/978-3-030-44689-5_18 CrossRefGoogle Scholar
Martinez, F., Pujana-Arrese, A., Retolaza, I., Sacristan, I., Basurko, J. and Landaluze, J.IKO: a five actuated DoF upper limb exoskeleton oriented to workplace assistance,” Appl. Bionics Biomech. 6(2), 143155 (2009). https://doi.org/10.1080/11762320902789871 CrossRefGoogle Scholar
Perry, J. C., Rosen, J. and Burns, S., “Upper-limb powered exoskeleton design,” IEEE/ASME Trans. Mechatron. 12(4), 408417 (2007). https://doi.org/10.1109/TMECH.2007.901934 CrossRefGoogle Scholar
Bullock, I. M., Borras, J. and Dollar, A. M., “Assessing assumptions in kinematic hand models: a review,” 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) (2012) pp. 139146. https://doi.org/10.1109/BioRob.2012.6290879 CrossRefGoogle Scholar
Derrick, T. R., “The effects of knee contact angle on impact forces and accelerations,” Med. Sci. Sports Exerc. 36(5), 832837 (2004). https://doi.org/10.1249/01.mss.0000126779.65353.cb CrossRefGoogle ScholarPubMed
Doheny, E. P., Lowery, M. M., FitzPatrick, D. P. and O“Malley, M. J., “Effect of elbow joint angle on force-EMG relationships in human elbow flexor and extensor muscles,” J. Electromyogr Kinesiol. 18(5), 760770 (2008). https://doi.org/10.1016/j.jelekin.2007.03.006 CrossRefGoogle ScholarPubMed
Hahn, D., Olvermann, M., Richtberg, J., Seiberl, W. and Schwirtz, A., “Knee and ankle joint torque-angle relationships of multi-joint leg extension,” J Biomech. 44(11), 20592065 (2011). https://doi.org/10.1016/j.jbiomech.2011.05.011 CrossRefGoogle ScholarPubMed
Oualkacha, K. and Rivest, L., “On the estimation of an average rigid body motion,” Biometrika 99(3), 585598 (2012). https://doi.org/10.1093/biomet/ass020 CrossRefGoogle Scholar
Medved, V., “Appendix 1: ISB recommendations for standardization in the reporting of kinematic data*,” In: Measurement of Human Locomotion (1st ed., CRC Press, Boca Raton, FL 2000) pp. 235242. https://doi.org/10.1201/9781420036985 CrossRefGoogle Scholar
Sheehan, F. T. and Mitiguy, P., “In regards to the ISB recommendations for standardization in the reporting of kinematic data,” J. Biomech. 32(10), 11351136 (1999). https://doi.org/10.1016/S0021-9290(99)00077-9 Google Scholar
Wu, G., Van Der Helm, F. C. T., Veeger, H. E. J., Makhsous, M., Van Roy, P., Anglin, C., Nagels, J., Karduna, A. R., McQuade, K., Wang, X., Werner, F. W. and Buchholz, B., “ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion - Part II: Shoulder, elbow, wrist and hand,” J. Biomech. 38(5), 981992 (2005). https://doi.org/10.1016/j.jbiomech.2004.05.042 CrossRefGoogle ScholarPubMed
Wu, G. and Cavanagh, P. R., “ISB recommendations for standardization in the reporting of kinematic data,” J. Biomech. 28(10), 12571261 (1995). https://doi.org/10.1016/0021-9290(95)00017-C CrossRefGoogle ScholarPubMed
Boston, J. R., Rudy, T. E., Mercer, S. R. and Kubinski, J. A., “A measure of body movement coordination during repetitive dynamic lifting,” IEEE Trans. Rehabil. Eng. 1(3), 137144 (1993). https://doi.org/10.1109/86.279263 CrossRefGoogle Scholar
Borbély, B. J. and Szolgay, P., “Real-time inverse kinematics for the upper limb: a model-based algorithm using segment orientations,” BioMed. Eng. 16, 21, 129 (2017). https://doi.org/10.1186/s12938-016-0291-x Google ScholarPubMed
Carpinella, I., Jonsdottir, J. and Ferrarin, M., “Multi-finger coordination in healthy subjects and stroke patients: a mathematical modelling approach,” J. NeuroEng. Rehabil. 8, 19, 119 (2011). https://doi.org/10.1186/1743-0003-8-19 CrossRefGoogle ScholarPubMed
Zhang, X. and Chaffin, D. B., “The effects of speed variation on joint kinematics during multisegment reaching movements,” Hum. Mov. Sci. 18, 741757 (1999). https://doi.org/10.1016/S0167-9457(99)00038-X CrossRefGoogle Scholar
Braido, P. and Zhang, X., “Quantitative analysis of finger motion coordination in hand manipulative and Gestic acts,” Hum. Mov. Sci. 22(6) 661678 (2004). https://doi.org/10.1016/j.humov.2003.10.001 CrossRefGoogle ScholarPubMed
Casey, J. and Lam, V. C., “A tensor method for the kinematical analysis of systems of Ridid bodies,” Mech. Mach. Theory 22(1), 8797 (1986). https://doi.org/10.1016/0094-114X(86)90032-7 CrossRefGoogle Scholar
Legnani, G., Casolo, F., Righettini, P. and Zappa, B., “A homogeneous matrix approach to 3D kinematics and dynamics – I. Theory,” Mech. Mach. Theory 3(5), 573587 (1996). https://doi.org/10.1016/0094-114X(95)00100-D CrossRefGoogle Scholar
Legnani, G., Casalo, F., Righettini, P. and Zappa, B., “A homogeneous matrix approach to 3D kinematics and dynamics – II. Applications to chains of rigid bodies and serial manipulators,” Mech. Mach. Theory 31(5), 589605 (1996). https://doi.org/10.1016/0094-114X(95)00101-4 CrossRefGoogle Scholar
Ahmad, A., Khan, S. and Anderson, K., “Kinematics and dynamics of a novel 6-DoF TAU haptic device,” 2011 IEEE International Conference on Mechatronics (ICM 2011) (2011) pp. 719724. https://doi.org/10.1109/ICMECH.2011.5971209 CrossRefGoogle Scholar
Lenarčič, J. and Umek, A., “A Pascal program for automatic generation of robot kinematic equations,” Robot. Comput. Integr. Manuf. 8(3), 149155 (1991). https://doi.org/10.1016/0736-5845(91)90014-J CrossRefGoogle Scholar
Miro, J. V. and White, A. S., “Modelling an industrial manipulator a case study,” Simul. Pract. Theory 9(6–8), 293319 (2002). https://doi.org/10.1016/S0928-4869(01)00046-5 CrossRefGoogle Scholar
Richard, M. J., McPhee, J. J. and Anderson, R. J., “Computerized generation of motion equations using variational graph-theoretic methods,” Appl. Math. Comput. 192(1), 135156 (2007). https://doi.org/10.1016/j.amc.2007.02.135 Google Scholar
Fleischer, J. and Krauße, M., “Physically consistent parameter optimization for the generation of pose independent simulation models using the example of a 6-axis articulated robot,” Procedia CIRP 12, pp. 217221 (2013). https://doi.org/10.1016/j.procir.2013.09.038 CrossRefGoogle Scholar
Mesquita, I. A., Pinheiro, A. R. V., Velhote Correia, M. F. P. and da Silva, C. I. C., “Methodological considerations for kinematic analysis of upper limbs in healthy and poststroke adults. Part I: a systematic review of sampling and motor tasks,” Top. Stroke Rehabil. 26(6), 142152 (2019). https://doi.org/10.1080/10749357.2018.1551953 CrossRefGoogle ScholarPubMed
Gull, M. A., Bai, S. and Bak, T., “A review on design of upper limb exoskeletons,” Robotics 9(1), 16, 135 (2020). https://doi.org/10.3390/robotics9010016 CrossRefGoogle Scholar
Stanišić, M. M. and Goehler, C. M., “Reproducing human arm motion using a kinematically coupled humanoid shoulder-elbow complex,” Appl. Bionics Biomech. 5(4), 175185 (2008). https://doi.org/10.1080/11762320802525128 CrossRefGoogle Scholar
Pang, Z., Wang, T., Wang, Z., Yu, J., Sun, Z. and Liu, S., “Design and analysis of a wearable upper limb rehabilitation robot with characteristics of tension mechanism,” Appl. Sci. 10(6), 2101, 122 (2020). https://doi.org/10.3390/app10062101 CrossRefGoogle Scholar
Krishnan, R., Björsell, N., Gutierrez-Farewik, E. M. and Smith, C., “A survey of human shoulder functional kinematic representations,” Med. Biol. Eng. Comput. 57, 339367 (2019). https://doi.org/10.1007/s11517-018-1903-3 CrossRefGoogle ScholarPubMed
Averta, G., Della Santina, C., Valenza, G., Bicchi, A. and Bianchi, M., “Exploiting upper-limb functional principal components for human-like motion generation of anthropomorphic robots,” J. NeuroEng. Rehabil. 17, 63, 115 (2020). https://doi.org/10.1186/s12984-020-00680-8 CrossRefGoogle ScholarPubMed
Picerno, P., Caliandro, P., Iacovelli, C., Simbolotti, C., Crabolu, M., Pani, D., Vannozzi, G., Reale, G., Rossini, P. M., Padua, L. and Cereatti, A., “Upper limb joint kinematics using wearable magnetic and inertial measurement units: an anatomical calibration procedure based on bony landmark identification,” Sci. Rep. 9, 14449, 110 (2019). https://doi.org/10.1038/s41598-019-50759-z CrossRefGoogle ScholarPubMed
Bertomeu-Motos, A., Lledó, L. D., Díez, J. A., Catalan, J. M., Ezquerro, S., Badesa, F. J. and Garcia-Aracil.Estimation of human arm joints using two wireless sensors in robotic rehabilitation tasks,” Sensors 15(2), 3057130583 (2015). https://doi.org/10.3390/s151229818 CrossRefGoogle ScholarPubMed
Bertomeu-Motos, A., Blanco, A., Badesa, F. J., Barios, J. A., Zollo, L. and Garcia-Aracil, N., “Human arm joints reconstruction algorithm in rehabilitation therapies assisted by end-effector robotic devices,” J. NeuroEng. Rehabil. 15, 10, 111 (2018). https://doi.org/10.1186/s12984-018-0348-0 CrossRefGoogle ScholarPubMed
Loh, B. G. and Rosen, J., “Kinematic analysis of 7 degrees of freedom upper-limb exoskeleton robot with tilted shoulder abduction,” Int. J. Precis. Eng. Manuf. 14, 6976 (2013). https://doi.org/10.1007/s12541-013-0011-4 CrossRefGoogle Scholar
Wang, Z., Cai, Z., Cui, L. and Pang, C., “Structure design and analysis of kinematics of an upper-limbed rehabilitation robot,” In: MATEC Web of Conferences 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018), October 12–14, 2018, Shanghai University of Engineering Science, China (Y. Wang and H. Chen, eds.), vol. 232 (EDP Sciences, 2018) p. 02033. https://doi.org/10.1051/matecconf/201823202033 CrossRefGoogle Scholar
Vaz, A., Kansal, H. and Singla, A., “Some aspects in the bond graph modelling of robotic manipulators: Angular velocities from symbolic manipulation of rotation matrices,” TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region, vol. 1 (2003) pp. 294–299. https://doi.org/10.1109/TENCON.2003.1273333 CrossRefGoogle Scholar
Bidard, C.Kinematic structure of mechanisms: a bond graph approach,” J. Franklin Inst. 328(5–6), 901915 (1991). https://doi.org/10.1016/0016-0032(91)90061-7 CrossRefGoogle Scholar
Romero, G., Félez, J., Martínez, M. L. and Maroto, J., “Kinematic analysis of mechanism by using bond-graph language,” In: 20th European Conference on Modelling and Simulation, Bonn, Germany, May 28–31, 2006: Modelling Methodologies and Simulation Key Technologies in Academia and Industry (W. Borutzky, A. Orsoni and R. Zobel, eds.) (European Council for Modeling and Simulation (ECMS), 2006) pp. 155165. ISBN: 0-9553018-0-7. http://dx.doi.org/10.7148/2006-0155 Google Scholar
Simo-Serra, E., Perez-Gracia, A., Moon, H., Robson, N., “Kinematic synthesis of multi-fingered robotic hands for finite and infinitesimal tasks,” In: Latest Advances in Robot Kinematics (J. Lenarcic and M. Husty, eds.) (Springer, Dordrecht, 2012) pp. 173180. https://doi.org/10.1007/978-94-007-4620-6_22 CrossRefGoogle Scholar
Upper Limb, Clinical Gate [Internet]. [cited 2021 Jul 22]. Available from: https://clinicalgate.com/upper-limb-2/.Google Scholar
Namdari, S., Yagnik, G., Ebaugh, D. D., Nagda, S., Ramsey, M. L., Williams, G. R. and Mehta, S., “Defining functional shoulder range of motion for activities of daily living,” J. Shoulder Elb. Surg. 21(9), 11771183 (2012). https://doi.org/10.1016/j.jse.2011.07.032 CrossRefGoogle ScholarPubMed
Palmer, A. K., Werner, F. W., Murphy, D. and Glisson, R., “Functional wrist motion: a biomechanical study,” J. Hand Surg. 10(1), 3946 (1985). https://doi.org/10.1016/S0363-5023(85)80246-X CrossRefGoogle ScholarPubMed
Safaee-Rad, R., Shwedyk, E., Quanbury, A. O. and Cooper, J. E., “Normal functional range of motion of upper limb joints during performance of three feeding activities,” Arch. Phys. Med. Rehabil. 71(7), 505509 (1990). PMID: 2350221.Google ScholarPubMed
Parida, P. K., Biswal, B. B. and Thatoi, D. N., “Kinematic analysis of an anthropomorphic robot hand,” Appl. Mech. Mater. 187, 293297 (2012). https://doi.org/10.4028/www.scientific.net/AMM.187.293 CrossRefGoogle Scholar
Aboul-Hagag, K. E., Mohamed, S. A., Hilal, M. A. and Mohamed, E. A.. “Determination of sex from hand dimensions and index/ring finger length ratio in Upper Egyptians,” Egypt. J. Forensic Sci. 1(2), 8086 (2011). https://doi.org/10.1016/j.ejfs.2011.03.001 CrossRefGoogle Scholar
Peña-Pitarch, E., Falguera, N. T. and Yang, J., (James). “Virtual human hand: model and kinematics,” Comput. Methods Biomech. Biomed. Eng. 17(5), 568579 (2014). https://doi.org/10.1080/10255842.2012.702864 CrossRefGoogle ScholarPubMed
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