上肢伸展姿势及运动轨迹预测
|
摘要
上肢伸展姿势及运动轨迹预测是工效学领域的前沿课题。目前已有的上肢伸展姿势及运动轨迹预测方法在预测准确性、自然性和实时性方面尚存在缺陷。本研究首先根据人体上肢和躯干的生理特点,对其进行了合理建模,并将站姿人体右侧上肢工作空间均匀划分为600个子区域,通过实时测量操作者执行上肢伸展运动的运动轨迹,引入曲线拟合和基于自组织映射理论的权重分布核函数相结合的方法,分别实现了站姿人体躯干非受限条件下,以典型定位运动(研究一)和快速定位运动(研究二)速度完成点对点指向任务、以典型定位运动速度完成按键任务(研究三)时,右手食指及达工作空间内任意目标位置的上肢伸展姿势及运动轨迹预测。整合上述结果,建立了基于任务的上肢伸展姿势及运动轨迹预测系统。该系统可直接应用于工效学领域计算机三维仿真人体的建立和发展,同时可直接应用于对航空航天座舱、核电站中央控制室、交通工具驾驶舱等的工效学设计与评价。
本研究获得了如下主要结论:
(1)执行上肢伸展运动时,上肢各关节对伸展运动所起的作用随时间而变化,且同一关节所含各自由度对伸展运动的贡献也存在差异。
(2)上肢伸展姿势及运动轨迹主要由及达目标所处的空间位置决定,但同时受伸展运动速度和控制器类型的影响。
(3)将曲线拟合和基于自组织映射理论的权重分布核函数相结合的方法,不仅适用于上肢伸展姿势及运动轨迹的预测,同时可为其他肢体部分运动轨迹的预测提供指导和借鉴作用。
(4)本研究所建立的基于任务的上肢伸展姿势及运动轨迹预测系统可满足工效学领域上肢伸展姿势及运动轨迹预测的准确性、自然性和实时性需要。
Upper body reach posture and trajectories prediction has been one of the focus topics. in the field of Human Factors. The existing predicting methods, however, should be improved in prediction accuracy, the attaiment of natural posture or trajectories and the real time of one prediction. The present study has adopted new perspectives into this field. In the first, the right arm and torso were specified as an eleven-degrees-of freedom kinematic linkage according to the human body physiological features. Secondly, the workplace was divided equally into 600 regions. Thirdly, based on real-time longitudinal data collected through three-dimensional motion capture system during the period of the right hand reaching 600 targets in the workplace, the fitting-curve method and the kernel function which stems from self-organization map theory were introduced to predict upper body reach posture and trjectories. The prediction was made in three conditions namely pointing the target button by natural speed Research i, pointing the botton by high speed Research ii and pushing the target button by natural speed Research iii . On the basis of those results, an upper body reach posture and trajectories prediction computer system was established. This system can be used in the simulation of upper body motion in computer three-dimensional human modeling, and also in ergonomic design evluation.
The main findings are as follows:
(1) Different parts of the right arm play different roles during the reach motion period, even the actions in different degrees-of-freedom of the same articulation are distinct.
(2) The reach posture and trajectories mainly depend on the target position, however they are also affected by the motion speed and the control type.
(3) The approach which integrating the workspace, curving fitting method and kernel functions can be used in upper body reach posture and trajectoties prdiction, and also can be introduced into modeling the motion of other body parts.
(4) The established upper body reach posture and trajectories prediction computer system can satisfy the ergonomics design and evaluation, because of its accuracy, naturalness and real-time prediciton.
本研究获得了如下主要结论:
(1)执行上肢伸展运动时,上肢各关节对伸展运动所起的作用随时间而变化,且同一关节所含各自由度对伸展运动的贡献也存在差异。
(2)上肢伸展姿势及运动轨迹主要由及达目标所处的空间位置决定,但同时受伸展运动速度和控制器类型的影响。
(3)将曲线拟合和基于自组织映射理论的权重分布核函数相结合的方法,不仅适用于上肢伸展姿势及运动轨迹的预测,同时可为其他肢体部分运动轨迹的预测提供指导和借鉴作用。
(4)本研究所建立的基于任务的上肢伸展姿势及运动轨迹预测系统可满足工效学领域上肢伸展姿势及运动轨迹预测的准确性、自然性和实时性需要。
Upper body reach posture and trajectories prediction has been one of the focus topics. in the field of Human Factors. The existing predicting methods, however, should be improved in prediction accuracy, the attaiment of natural posture or trajectories and the real time of one prediction. The present study has adopted new perspectives into this field. In the first, the right arm and torso were specified as an eleven-degrees-of freedom kinematic linkage according to the human body physiological features. Secondly, the workplace was divided equally into 600 regions. Thirdly, based on real-time longitudinal data collected through three-dimensional motion capture system during the period of the right hand reaching 600 targets in the workplace, the fitting-curve method and the kernel function which stems from self-organization map theory were introduced to predict upper body reach posture and trjectories. The prediction was made in three conditions namely pointing the target button by natural speed Research i, pointing the botton by high speed Research ii and pushing the target button by natural speed Research iii . On the basis of those results, an upper body reach posture and trajectories prediction computer system was established. This system can be used in the simulation of upper body motion in computer three-dimensional human modeling, and also in ergonomic design evluation.
The main findings are as follows:
(1) Different parts of the right arm play different roles during the reach motion period, even the actions in different degrees-of-freedom of the same articulation are distinct.
(2) The reach posture and trajectories mainly depend on the target position, however they are also affected by the motion speed and the control type.
(3) The approach which integrating the workspace, curving fitting method and kernel functions can be used in upper body reach posture and trajectoties prdiction, and also can be introduced into modeling the motion of other body parts.
(4) The established upper body reach posture and trajectories prediction computer system can satisfy the ergonomics design and evaluation, because of its accuracy, naturalness and real-time prediciton.
引文
Abdel, M.K., Yu, W, & Jaber, M. (2002). Realistic Posture Prediction for maximum dexterity. SAE Transactions Journal of Passenger Cars Mechanical System. 110(6):2241-2249
Abend, W., Bizzi, E. & Morasso, P. (1982). Human arm trajectory formation. Brain. 105(2):331-348
Atkeson, C.G., Hollerbach, J.M. (1985). Kinematic features of unstrained vertical arm movements. Journal of Neuroscience. 5(9):2318-2330
Badler N.I., Phillips C.B., & Webber B.L. (1993). Simulating Humans-Computer Graphics Animation and Control. Oxford: Oxford University Press. 85-96
Beck, D.J., Chaffin, D.B. (1992). An evaluation of inverse kinematics models for posture prediction. In: Mattila, M., Karwowski, W. Computer Applications in Ergonomics, Occupational Safety and Health, Amsterdam: Elsevier. 329-336
Bernstein, N. (1967). The coordination and regulation movements. New York: Pergamon Press.
Case, K.J., Porter, M., & Bonney, M.C. (1990). SAMMIE: A man and workplace modeling system. In: Karwowsk W, Genaidy A.M, &Asfour S.S. Computer-Aided Ergonomics. London: Taylor and Francis. 31-56
Chaffin, D. B, Faraway, J. J. (2000). Stature, age, and gender effects on reach motion postures. Human Factors. 42(3):408-420
Chaffin, D.B., Faraway, J.J., & Zhang, X.D. (1999). Simulating reach motions. SAE Human Modeling for Design and Engineering Conference, Hague, Netherlands.
Dooley, M. (1982). Anthropometric modeling program - a survey. IEEE Computer Graphics and Applications. 2(1): 17-25
Dysart, M.J., Woldstad, J.C. (1996). Posture prediction for static sagittal-plane lifting. Journal of Biomechanics. 29(10): 1393-1397
Eksioglu, M., Fernandez, J.E., & Twomey, J.M. (1996). Predicting peak pinch strength: artificial neural networks vs regression. International Journal of Industrial Ergonomics. 18(5-6): 431-441
Fabrice, S., Jean, B., & Jean, L. V. etc. (2004). Online control of the direction of rapid reaching movements. Experimental Brain Research. 157:468-471
Faraway, J.J. (1997). Regression analysis for a functional response. Technometrics. 39(3):254-261
Faraway, J.J. (2000). Modeling reach motions using functional regression. Digital Human Modeling for Design and Engineering Conference and Exposition, Michigan.
Faraway, J.J.(2001a). Modeling hand trajectories during reaching motions. Technical Report, Department of Statistics, Michigan University. 1-16
Faraway, J.J. (2001b). Regression Modeling of Motion with Endpoint Constraints. Journal of Visualization and Computer Animation. 14(1):31-41
Faraway, J.J.,& Hu,J. (2001). Modeling Variability in reaching motion. SAE Digital Human Modeling Conference, Arlington, VA.
Faraway, J.J. (2004). Human animation using nonparametric regression. Journal of computational and Graphical Statistics. 13(3):537-553
Flanagan, J.R., David, J.O. (1990). Trajectories of human multi-joint arm movements: evidence of joint level planning. In: Khatib, O. Hayward, V. Experimental Robotics 1.New York: Springer.594-613
Flash, T., Hogan, N. (1985). The coordination of arm movement: an experimental confirmed mathematical model. Journal of Neuroscience. 5(7): 1688-1703
Haggard, P., Richardson, J. (1996). Spatial patterns in the control of human arm movement. Journal of Experimental Psychology: Human Perception and Performance. 22 (1):42-62
Hestenes, D. (1994). Invariant body kinematics. II: reaching and neurogeometry. Neural Networks.7(1): 79-88
Hogfors, C., Sigholm, G.,& Herberts, P. (1987). Biomechanical model of the human shoulder-I: Elements. Journal of Biomechanics. 20(2):157-166.
Hollerbach, J.M., Flash, T. (1982). Dynamic interactions between limb segments during planar arm movement. Biological Cybernetics. 44:67-77
Hsiao, H., Keyserling, W.M. (1991). Evaluating posture behaviour during seated tasks. International Journal of Industrial Ergonomics. 80:313-334
Jung, E.S., Choe, J. (1996). Human reach posture prediction based on psychophysical discomfort. International Journal of Industrial Ergonomics. 18(2-3): 173-179
Jung E.S., Kee, D. (1996). A man-machine interface model with improved visibility and reach functions. Computers and industrial engineering. 30(3):475-486
Jung, E.S., Kee, D.,& Chung, M.K. (1992). Reach posture prediction of upper limb for ergonomic workplace evaluation. In: Proceedings of the Human Factors Society 36~(th) Annual Meeting, Human Factors Society: Santa Monica.702-706
Jung, E.S., Kee, D.,& Chung, M.K. (1995). Upper body reach posture prediction for ergonomic evaluation models. International Journal of Industrial Ergonomics. 16(2): 95-107
Jung, E.S., Park,S. (1994). Prediction of human reach posture using a neural network for ergonomic man models.Computers and Industrial Engineering. 27(1-4): 369-372
Kaminski, T., Gentile, A.M. (1986). Joint control strategies and hand trajectories in multijoint pointing movements. Journal of Motor Behavior. 18(3):261-278
Kaminski, T.R., Bock, C.,& Gentile, A. M. (1995). The coordination between trunk and arm motion during pointing movements. Experimental Brain Research. 106(3):457-466
Karl, H.E.K., Stover, H.S., &Susan, K.M., etc. (1988). Ergonomic models of anthropometry, human biomechanics and operator equipment interfaces: Proceedings of a workshop. Committee on human factors, National research council.43-64
Kee, D. (2001). LUBA: an assessment technique for postural loading on the upper body based on joint motion discomfort and maximum holding time. Applied Ergonomics.32(4):357-366
Kee, D. (2002). A method for analytically generating three-dimensional isocomfort workspace based on perceived discomfort. Applied Ergonomics. 33(1):51-62
Kim, J.H., Abdel-Malek, K., & Yang, J. (2004). Dynamic motion prediction and energy level determination for a virtual soldier's upperbody.http://www.dtic.mil/ndia/2004issc/thursday/kim.ppt
KIISA, C.N., SARA, M., & MARTHA, F. (1999). Do arm postures vary with the speed of reaching. Journal of Neurophysiology. 81(5):2582-2586
Kingsley, E.C., Schofield, N.A., & Case, K. (1981). A computer aid for man machine modeling. Computer Graphics. 15(3): 163-169
Kohonen,T.,(1982). Self-Organized formation of topologically correct feature maps. Biological Cybernetics. 43(2):59-69
Kuperstein, M. (1988). Neural model of adaptive hand-eye coordination for single postures. Science. 239(4845):1308-1311
Lauren, E.S., Stephen, H.S. (1998). Hand and joint paths during reaching movements with and without vision. Experimental Brain Research. 122(2): 157-164
Lepoutre, F.X. (1993). Human posture modelization as a problem of inverse kinematic of redundant robots. Robotica. 11:339-343
Mary,D.K.B., Ruud, G.J.M..& Stan, C.A.M.G.(1998). Geometric features of workspace and joint-space paths of 3D reaching movements. Acta Psychologica. 100(1-2): 37-53
Maurel, W. (1999). 3D Modelling of the human upper limb including the biomechanics of joints, muscles and soft tissues. Ph.D. Thesis, Ecole Polytechnique Federate de Lausanne, France
Mi, Z. (2004). Digital human modeling and simulation. Ph.D. Thesis, University of Iowa, USA.
Morasso, P. (1981). Spatial control of arm movements. Experimental Brain Research. 42(2): 223-227
Morasso, P. (1983). Three dimensional arm trajectory. Biological Cybernetics. 48:187-194
Oyama,E., Agah,A., & MacDorman, K.F.,etc. (2001). A modular neural network architecture for inverse kinematics model learning. Neurocomputing. 38-400:797-805
Schillings, J.J., Meulenbroek, R.G.J., & Thomassen, A.J.W.M. (1996). Limb segment recruitment as a function of movement direction, amplitude, and speed. Journal of Motor Behavior. 28 (3):241-254.
Rodriguez, I., Peinado, M.,& Boulic, R., etc. (2003). Bringing the human arm reachable space to a virtual environment for its analysis.In: Multimedia and Expo, 2003. ICME '03. Proceedings. 1(1 - 2):29-32
Soechting, J.F., Lacquaniti, F.(1981). Invariant characteristics of a pointing movement in man. Journal of Neuroscience. 1(7):710-720
Tolani, D., Goswami, A., &Badler, N. (2000). Real-time inverse kinematics techniques for anthropomorphic limbs. Graphical Models. 62(5):353-388
Wang, X.G. (1999). A behavior-based inverse kinematics algorithm to predict arm prehension postures for computer-aided ergonomic evaluation. Journal of Biomechanics. 32():453-460
Wang, X.G., Verriest, J.P. (1998). A geometric algorithm to predict the arm reach posture for computer-aided ergonomic evaluation. Journal of Visual Computer Animation. 9(2):33-47
Zakotnik, J., Matheson, T.& Durr, V.(2004). A posture optimization algorithm for model-based motion capture of movement sequences.Journal of Neuroscience Methods.135:43-54
Zhang,X.Chaff.m,D.B.(1997).Task effects on three-dimensional dynamic postures during seated reaching movements:an investigation scheme and illustration.Human Factors.39:659-67
Zhang,X.,Chaffin,D.B.(2000).A three-dimensional dynamic posture prediction model for simulating in-vehicle seated reaching movements:development and validation.Ergonomics.43(9):1314-1330
Zhang,X.D.,Kuo,A.D.,& Chaffin,D.B.(1998).Optimization-based differential kinematic modeling exhibits a velocity-control strategy for dynamic posture determination in seated reaching movements.Journal of Biomechanics.31(11):1035-1042
Zhao,J.,Badler,N.(1994).Inverse kinematics positioning using nonlinear programming for highly articulated figures.ACM Transactions on Graphics.13(4):313-336
高磊 张德运 赵东平等.(2004),自适应散列映射的弱跳完整性研究.西安交通大学学报.38(2):1232-1235
郭璐 沈模卫 陈硕.(2005).上肢伸展姿势预测研究进展.人类工效学.11(2):56-59
郭璐 沈模卫 关忻.(2005).函数回归方法在肢体运动轨迹预测中的应用.心理科学.28(3):660-662
李庆扬 关治 白峰杉.(2000).数值计算原理.第一版.北京:清华大学出版社.
刘顺忠.(2005).数理统计理论、方法、应用和软件计算.第一版.武汉:华中科技大学出版社.
邵象清.(1985).人体测量手册.第一版.上海:上海辞书出版社.
吴环成.(2005).关节的近侧环节及其运动.解剖学杂志.28(1):17,64
王丽君 姚鸿勋 刘绍辉等.(2005).压缩域自适应映射能量视频水印算法.计算机学报.28(11):1-12
中华人民共和国国家标准.GBl0000.中国成年人人体尺寸.(1988).北京:中国标准出版社.
中华人民共和国国家标准.GB5703-85.人体测量方法.(1985).北京:中国标准出版社.
中华人民共和国国家标准.GB3975-83.人体测量术语.北京:中国标准出版社.
中华人民共和国国家标准.GB5704.1-5704.4-85.人体测量仪器.北京:中国标准出版社.
朱祖祥等.(1994).人类工效学.第一版.杭州:浙江教育出版社.
Abend, W., Bizzi, E. & Morasso, P. (1982). Human arm trajectory formation. Brain. 105(2):331-348
Atkeson, C.G., Hollerbach, J.M. (1985). Kinematic features of unstrained vertical arm movements. Journal of Neuroscience. 5(9):2318-2330
Badler N.I., Phillips C.B., & Webber B.L. (1993). Simulating Humans-Computer Graphics Animation and Control. Oxford: Oxford University Press. 85-96
Beck, D.J., Chaffin, D.B. (1992). An evaluation of inverse kinematics models for posture prediction. In: Mattila, M., Karwowski, W. Computer Applications in Ergonomics, Occupational Safety and Health, Amsterdam: Elsevier. 329-336
Bernstein, N. (1967). The coordination and regulation movements. New York: Pergamon Press.
Case, K.J., Porter, M., & Bonney, M.C. (1990). SAMMIE: A man and workplace modeling system. In: Karwowsk W, Genaidy A.M, &Asfour S.S. Computer-Aided Ergonomics. London: Taylor and Francis. 31-56
Chaffin, D. B, Faraway, J. J. (2000). Stature, age, and gender effects on reach motion postures. Human Factors. 42(3):408-420
Chaffin, D.B., Faraway, J.J., & Zhang, X.D. (1999). Simulating reach motions. SAE Human Modeling for Design and Engineering Conference, Hague, Netherlands.
Dooley, M. (1982). Anthropometric modeling program - a survey. IEEE Computer Graphics and Applications. 2(1): 17-25
Dysart, M.J., Woldstad, J.C. (1996). Posture prediction for static sagittal-plane lifting. Journal of Biomechanics. 29(10): 1393-1397
Eksioglu, M., Fernandez, J.E., & Twomey, J.M. (1996). Predicting peak pinch strength: artificial neural networks vs regression. International Journal of Industrial Ergonomics. 18(5-6): 431-441
Fabrice, S., Jean, B., & Jean, L. V. etc. (2004). Online control of the direction of rapid reaching movements. Experimental Brain Research. 157:468-471
Faraway, J.J. (1997). Regression analysis for a functional response. Technometrics. 39(3):254-261
Faraway, J.J. (2000). Modeling reach motions using functional regression. Digital Human Modeling for Design and Engineering Conference and Exposition, Michigan.
Faraway, J.J.(2001a). Modeling hand trajectories during reaching motions. Technical Report, Department of Statistics, Michigan University. 1-16
Faraway, J.J. (2001b). Regression Modeling of Motion with Endpoint Constraints. Journal of Visualization and Computer Animation. 14(1):31-41
Faraway, J.J.,& Hu,J. (2001). Modeling Variability in reaching motion. SAE Digital Human Modeling Conference, Arlington, VA.
Faraway, J.J. (2004). Human animation using nonparametric regression. Journal of computational and Graphical Statistics. 13(3):537-553
Flanagan, J.R., David, J.O. (1990). Trajectories of human multi-joint arm movements: evidence of joint level planning. In: Khatib, O. Hayward, V. Experimental Robotics 1.New York: Springer.594-613
Flash, T., Hogan, N. (1985). The coordination of arm movement: an experimental confirmed mathematical model. Journal of Neuroscience. 5(7): 1688-1703
Haggard, P., Richardson, J. (1996). Spatial patterns in the control of human arm movement. Journal of Experimental Psychology: Human Perception and Performance. 22 (1):42-62
Hestenes, D. (1994). Invariant body kinematics. II: reaching and neurogeometry. Neural Networks.7(1): 79-88
Hogfors, C., Sigholm, G.,& Herberts, P. (1987). Biomechanical model of the human shoulder-I: Elements. Journal of Biomechanics. 20(2):157-166.
Hollerbach, J.M., Flash, T. (1982). Dynamic interactions between limb segments during planar arm movement. Biological Cybernetics. 44:67-77
Hsiao, H., Keyserling, W.M. (1991). Evaluating posture behaviour during seated tasks. International Journal of Industrial Ergonomics. 80:313-334
Jung, E.S., Choe, J. (1996). Human reach posture prediction based on psychophysical discomfort. International Journal of Industrial Ergonomics. 18(2-3): 173-179
Jung E.S., Kee, D. (1996). A man-machine interface model with improved visibility and reach functions. Computers and industrial engineering. 30(3):475-486
Jung, E.S., Kee, D.,& Chung, M.K. (1992). Reach posture prediction of upper limb for ergonomic workplace evaluation. In: Proceedings of the Human Factors Society 36~(th) Annual Meeting, Human Factors Society: Santa Monica.702-706
Jung, E.S., Kee, D.,& Chung, M.K. (1995). Upper body reach posture prediction for ergonomic evaluation models. International Journal of Industrial Ergonomics. 16(2): 95-107
Jung, E.S., Park,S. (1994). Prediction of human reach posture using a neural network for ergonomic man models.Computers and Industrial Engineering. 27(1-4): 369-372
Kaminski, T., Gentile, A.M. (1986). Joint control strategies and hand trajectories in multijoint pointing movements. Journal of Motor Behavior. 18(3):261-278
Kaminski, T.R., Bock, C.,& Gentile, A. M. (1995). The coordination between trunk and arm motion during pointing movements. Experimental Brain Research. 106(3):457-466
Karl, H.E.K., Stover, H.S., &Susan, K.M., etc. (1988). Ergonomic models of anthropometry, human biomechanics and operator equipment interfaces: Proceedings of a workshop. Committee on human factors, National research council.43-64
Kee, D. (2001). LUBA: an assessment technique for postural loading on the upper body based on joint motion discomfort and maximum holding time. Applied Ergonomics.32(4):357-366
Kee, D. (2002). A method for analytically generating three-dimensional isocomfort workspace based on perceived discomfort. Applied Ergonomics. 33(1):51-62
Kim, J.H., Abdel-Malek, K., & Yang, J. (2004). Dynamic motion prediction and energy level determination for a virtual soldier's upperbody.http://www.dtic.mil/ndia/2004issc/thursday/kim.ppt
KIISA, C.N., SARA, M., & MARTHA, F. (1999). Do arm postures vary with the speed of reaching. Journal of Neurophysiology. 81(5):2582-2586
Kingsley, E.C., Schofield, N.A., & Case, K. (1981). A computer aid for man machine modeling. Computer Graphics. 15(3): 163-169
Kohonen,T.,(1982). Self-Organized formation of topologically correct feature maps. Biological Cybernetics. 43(2):59-69
Kuperstein, M. (1988). Neural model of adaptive hand-eye coordination for single postures. Science. 239(4845):1308-1311
Lauren, E.S., Stephen, H.S. (1998). Hand and joint paths during reaching movements with and without vision. Experimental Brain Research. 122(2): 157-164
Lepoutre, F.X. (1993). Human posture modelization as a problem of inverse kinematic of redundant robots. Robotica. 11:339-343
Mary,D.K.B., Ruud, G.J.M..& Stan, C.A.M.G.(1998). Geometric features of workspace and joint-space paths of 3D reaching movements. Acta Psychologica. 100(1-2): 37-53
Maurel, W. (1999). 3D Modelling of the human upper limb including the biomechanics of joints, muscles and soft tissues. Ph.D. Thesis, Ecole Polytechnique Federate de Lausanne, France
Mi, Z. (2004). Digital human modeling and simulation. Ph.D. Thesis, University of Iowa, USA.
Morasso, P. (1981). Spatial control of arm movements. Experimental Brain Research. 42(2): 223-227
Morasso, P. (1983). Three dimensional arm trajectory. Biological Cybernetics. 48:187-194
Oyama,E., Agah,A., & MacDorman, K.F.,etc. (2001). A modular neural network architecture for inverse kinematics model learning. Neurocomputing. 38-400:797-805
Schillings, J.J., Meulenbroek, R.G.J., & Thomassen, A.J.W.M. (1996). Limb segment recruitment as a function of movement direction, amplitude, and speed. Journal of Motor Behavior. 28 (3):241-254.
Rodriguez, I., Peinado, M.,& Boulic, R., etc. (2003). Bringing the human arm reachable space to a virtual environment for its analysis.In: Multimedia and Expo, 2003. ICME '03. Proceedings. 1(1 - 2):29-32
Soechting, J.F., Lacquaniti, F.(1981). Invariant characteristics of a pointing movement in man. Journal of Neuroscience. 1(7):710-720
Tolani, D., Goswami, A., &Badler, N. (2000). Real-time inverse kinematics techniques for anthropomorphic limbs. Graphical Models. 62(5):353-388
Wang, X.G. (1999). A behavior-based inverse kinematics algorithm to predict arm prehension postures for computer-aided ergonomic evaluation. Journal of Biomechanics. 32():453-460
Wang, X.G., Verriest, J.P. (1998). A geometric algorithm to predict the arm reach posture for computer-aided ergonomic evaluation. Journal of Visual Computer Animation. 9(2):33-47
Zakotnik, J., Matheson, T.& Durr, V.(2004). A posture optimization algorithm for model-based motion capture of movement sequences.Journal of Neuroscience Methods.135:43-54
Zhang,X.Chaff.m,D.B.(1997).Task effects on three-dimensional dynamic postures during seated reaching movements:an investigation scheme and illustration.Human Factors.39:659-67
Zhang,X.,Chaffin,D.B.(2000).A three-dimensional dynamic posture prediction model for simulating in-vehicle seated reaching movements:development and validation.Ergonomics.43(9):1314-1330
Zhang,X.D.,Kuo,A.D.,& Chaffin,D.B.(1998).Optimization-based differential kinematic modeling exhibits a velocity-control strategy for dynamic posture determination in seated reaching movements.Journal of Biomechanics.31(11):1035-1042
Zhao,J.,Badler,N.(1994).Inverse kinematics positioning using nonlinear programming for highly articulated figures.ACM Transactions on Graphics.13(4):313-336
高磊 张德运 赵东平等.(2004),自适应散列映射的弱跳完整性研究.西安交通大学学报.38(2):1232-1235
郭璐 沈模卫 陈硕.(2005).上肢伸展姿势预测研究进展.人类工效学.11(2):56-59
郭璐 沈模卫 关忻.(2005).函数回归方法在肢体运动轨迹预测中的应用.心理科学.28(3):660-662
李庆扬 关治 白峰杉.(2000).数值计算原理.第一版.北京:清华大学出版社.
刘顺忠.(2005).数理统计理论、方法、应用和软件计算.第一版.武汉:华中科技大学出版社.
邵象清.(1985).人体测量手册.第一版.上海:上海辞书出版社.
吴环成.(2005).关节的近侧环节及其运动.解剖学杂志.28(1):17,64
王丽君 姚鸿勋 刘绍辉等.(2005).压缩域自适应映射能量视频水印算法.计算机学报.28(11):1-12
中华人民共和国国家标准.GBl0000.中国成年人人体尺寸.(1988).北京:中国标准出版社.
中华人民共和国国家标准.GB5703-85.人体测量方法.(1985).北京:中国标准出版社.
中华人民共和国国家标准.GB3975-83.人体测量术语.北京:中国标准出版社.
中华人民共和国国家标准.GB5704.1-5704.4-85.人体测量仪器.北京:中国标准出版社.
朱祖祥等.(1994).人类工效学.第一版.杭州:浙江教育出版社.