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2016, Number 2

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Rev Mex Ing Biomed 2016; 37 (2)

Comparación de dos sistemas de captura de movimiento por medio de las trayectorias articulares de marcha

Bravo MDA, Rengifo RCF, Agredo RW

Language: Spanish
References: 28
Page: 149-160
PDF size: 872.97 Kb.


ABSTRACT

Currently, the most common methods for proper capture of human movement in three dimensions require alaboratory environment and setting markers, accessories or sensors to the body segments. However, the high cost ofthis equipment is a limiting factor in diverse environments. Motion capture systems such as Microsoft KinectTMpresentan alternative approach to motion capture technology.
In this paper, two motion capture systems are compared by means of joint trajectories and anthropometricmeasurements of a person in a normal gait cycle. The first is accurate trading system that uses markers (ViconTM), andthe second is Microsoft KinectTMcamera. Both systems were evaluated in order to compare the geometric differenceand the RMS error between the joint human walking paths obtained for each of the systems. The results show agreater variance in anthropometric measures and joint trajectories for Kinect, although this system is inexpensiveand easy to use and install, cannot be used for precise kinematic analysis of human walking.


REFERENCES

  1. [1] K. Abdel-Malek and J. Arora,Human Motion Simulation: PredictiveDynamics. Elsevier Science, 2013.

  2. [2] K. Adistambha, C. Ritz, and I. Burnett,“Motion classification using dynamictime warping,” inMultimedia SignalProcessing, 2008 IEEE 10th Workshopon, Oct 2008, pp. 622–627.

  3. [3] K. Ayusawa and Y. Nakamura, “Fastinverse kinematics algorithm forlarge dof system with decomposedgradient computation based onrecursive formulation of equilibrium,”inIntelligent Robots and Systems(IROS), 2012 IEEE/RSJ InternationalConference on, Oct 2012, pp. 3447–3452.

  4. [4] A. Cappozzo, A. Cappello, U. d. Croce,and F. Pensalfini, “Surface-markercluster design criteria for 3-dbone movement reconstruction,” inBiomedical Engineering, 1997.

  5. [5] C. Chevallerau, G. Bessonnet, G. Abba,and Y. Aoustin,Bipedal Robots.Modeling, design and building walkingrobots, 1st ed. Wiley, 2009.

  6. [6] M. P. A. Chris Kirtley,Clinical GaitAnalysis. Theory and Practice, 1st ed.Churchill Livingstone, 2006.

  7. [7] R. A. Clark, K. J. Bower, B. F.Mentiplay, K. Paterson, and Y.-H. Pua,“Concurrent validity of the microsoftkinect for assessment of spatiotemporalgait variables,”Journal of Biomechanics,vol. 46, no. 15, pp. 2722 – 2725, 2013.

  8. [8] R. A. Clark, Y.-H. Pua, K. Fortin,C. Ritchie, K. E. Webster, L. Denehy,and A. L. Bryant, “Validity of themicrosoft kinect for assessment ofpostural control,”Gait & Posture,vol. 36, no. 3, pp. 372 – 377, 2012.

  9. [9] P. I. Corke,Robotics, vision and control: fundamental algorithms in Matlab,1st ed., ser. Star, 73.; Springer tracts inadvanced robotics, 73. Springer, 2011.

  10. [10] B. Damas and J. Santos-Victor, “Anonline algorithm for simultaneouslylearningforwardandinversekinematics,” inIntelligent Robotsand Systems (IROS), 2012 IEEE/RSJInternational Conference on, Oct 2012,pp. 1499–1506.

  11. [11] J. Denavit and R. S. Hartenberg,“A kinematic notation for lower-pairmechanisms based on matrices,”Trans.ASME, J. Appl. Mech., vol. 22, no. 2, pp.215 – 221, 1965.

  12. [12] G. Du, P. Zhang, J. Mai, and Z. Li.,“Markerless kinect-based hand trackingfor robot teleoperation.”InternationalJournal of Advanced Robotic Systems,2012.

  13. [13] T. Dutta, “Evaluation of the kinectsensor for 3-d kinematic measurementin the workplace,”Applied Ergonomics,vol. 43, no. 4, pp. 645 – 649, 2012.

  14. [14] J. P. Holden, J. A. Orsini, K. L.Siegel, T. M. Kepple, L. H. Gerber,and S. J. Stanhope, “Surface movementerrors in shank kinematics and kneekinetics during gait,”Gait & Posture,vol. 5, no. 3, pp. 217 – 227, 1997.

  15. [15] V. Ivancevic and T. Ivancevic,Human-Like Biomechanics: A UnifiedMathematical Approach to HumanBiomechanics and Humanoid Robotics,ser. Intelligent Systems, Control andAutomation: Science and Engineering,v. 28. Springer, 2008.

  16. [16] S. Izadi, D. Kim, O. Hilliges,D. Molyneaux, R. Newcombe, P. Kohli,J. Shotton, S. Hodges, D. Freeman,A. Davison, and A. Fitzgibbon, “Kinect-fusion: Real-time 3d reconstruction and interaction using a moving depthcamera,” inProceedings of the 24thAnnual ACM Symposium on UserInterface Software and Technology, ser.UIST ’11. New York, NY, USA: ACM,2011, pp. 559–568.

  17. [17] W. Khalil and E. Dombre,Modeling,Identification and Control of Robots,2nd ed., ser. Kogan Page Science. Paris,France: Butterworth - Heinemann, 2004.

  18. [18] S. J. Lee, Y. Motai, and H. Choi,“Tracking human motion withmultichannel interacting multiplemodel,”Industrial Informatics, IEEETransactions on, vol. 9, no. 3, pp.1751–1763, Aug 2013.

  19. [19] M. J. Malinowski, E. Matsinos, andS. Roth, “On using the MicrosoftKinectTMsensors in the analysis ofhuman motion,”ArXiv e-prints, Dec.2014.

  20. [20] C. D. Mutto, P. Zanuttigh, and G. M.Cortelazzo,Time-of-Flight Camerasand Microsoft Kinect(TM). SpringerPublishing Company, Incorporated,2012.

  21. [21] L. Rabiner and B.-H. Juang,Fundamentals of Speech Recognition.Upper Saddle River, NJ, USA: Prentice-Hall, Inc., 1993.

  22. [22] C. Reinschmidt, A. van den Bogert,B. Nigg, A. Lundberg, and N. Murphy,“Effect of skin movement on the analysisof skeletal knee joint motion duringrunning,”Journal of Biomechanics,vol. 30, pp. 729–732, 1997.

  23. [23] A. Schmitz, M. Ye, R. Shapiro, R. Yang,and B. Noehren, “Accuracy andrepeatability of joint angles measuredusing a single camera markerlessmotion capture system,”Journal ofBiomechanics, vol. 47, no. 2, pp. 587 –591, 2014.

  24. [24] L. A. Schwarz, A. Mkhitaryan,D. Mateus, and N. Navab, “Humanskeleton tracking from depth data usinggeodesic distances and optical flow,”Image and Vision Computing, vol. 30,no. 3, pp. 217 – 226, 2012.

  25. [25] E. Stone and M. Skubic, “Passive in-home measurement of stride-to-stridegait variability comparing vision andkinect sensing,” inEngineering inMedicine and Biology Society,EMBC,2011 Annual International Conference ofthe IEEE, Aug 2011, pp. 6491–6494.

  26. [26] H. Toshani and M. Farrokhi, “Real-time inverse kinematics of redundantmanipulators using neural networksand quadratic programming: Alyapunov-based approach,”Roboticsand Autonomous Systems, vol. 62, no. 6,pp. 766 – 781, 2014.

  27. [27] J.-T. Zhang, A. C. Novak, B. Brouwer,and Q. Li, “Concurrent validation ofxsens mvn measurement of lower limbjoint angular kinematics,”PhysiologicalMeasurement, vol. 34, no. 8, p. N63,2013.

  28. [28] F. Zhou and F. De la Torre, “Generalizedtime warping for multi-modal alignmentof human motion,” inComputer Visionand Pattern Recognition (CVPR), 2012IEEE Conference on, June 2012, pp.1282–1289




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