2016, Número 2
<< Anterior
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
Idioma: Español
Referencias bibliográficas: 28
Paginas: 149-160
Archivo PDF: 872.97 Kb.
RESUMEN
En la actualidad, los métodos más comunes para una adecuada captura del movimiento humano en tresdimensiones requieren de un entorno de laboratorio y la fijación de marcadores, accesorios o sensores a los segmentoscorporales. Sin embargo, el alto costo de estos equipos es un factor limitante en diversos entornos de trabajo. Sistemasde captura de movimiento como Microsoft Kinect
TMpresentan un enfoque alternativo a la tecnología de captura demovimiento.
En este trabajo se comparan dos sistemas de captura de movimiento por medio de las trayectorias articulares y lasmedidas antropométricas de una persona en un ciclo de marcha normal. El primero de ellos, es un sistema comercialde precisión que utiliza marcadores (Vicon
TM) y el segundo, es la cámara Microsoft Kinect
TM. Ambos sistemas seevaluaron con el propósito de comparar la diferencia geométrica y el error RMS entre las trayectorias articularesde la marcha humana obtenidas por cada uno de los sistemas. Los resultados muestran una varianza mayor en lasmedidas antropométricas y trayectorias articulares para el Kinect, aunque este sistema es de bajo costo y de fáciluso e instalación, no puede ser utilizado para un análisis preciso de la cinemática de la marcha humana.
REFERENCIAS (EN ESTE ARTÍCULO)
[1] K. Abdel-Malek and J. Arora,Human Motion Simulation: PredictiveDynamics. Elsevier Science, 2013.
[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] 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] A. Cappozzo, A. Cappello, U. d. Croce,and F. Pensalfini, “Surface-markercluster design criteria for 3-dbone movement reconstruction,” inBiomedical Engineering, 1997.
[5] C. Chevallerau, G. Bessonnet, G. Abba,and Y. Aoustin,Bipedal Robots.Modeling, design and building walkingrobots, 1st ed. Wiley, 2009.
[6] M. P. A. Chris Kirtley,Clinical GaitAnalysis. Theory and Practice, 1st ed.Churchill Livingstone, 2006.
[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] 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] P. I. Corke,Robotics, vision and control: fundamental algorithms in Matlab,1st ed., ser. Star, 73.; Springer tracts inadvanced robotics, 73. Springer, 2011.
[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] 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] G. Du, P. Zhang, J. Mai, and Z. Li.,“Markerless kinect-based hand trackingfor robot teleoperation.”InternationalJournal of Advanced Robotic Systems,2012.
[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] 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] 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] 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] W. Khalil and E. Dombre,Modeling,Identification and Control of Robots,2nd ed., ser. Kogan Page Science. Paris,France: Butterworth - Heinemann, 2004.
[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] M. J. Malinowski, E. Matsinos, andS. Roth, “On using the MicrosoftKinectTMsensors in the analysis ofhuman motion,”ArXiv e-prints, Dec.2014.
[20] C. D. Mutto, P. Zanuttigh, and G. M.Cortelazzo,Time-of-Flight Camerasand Microsoft Kinect(TM). SpringerPublishing Company, Incorporated,2012.
[21] L. Rabiner and B.-H. Juang,Fundamentals of Speech Recognition.Upper Saddle River, NJ, USA: Prentice-Hall, Inc., 1993.
[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] 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] 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] 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] 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] 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] 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