Literatura académica sobre el tema "Human gait model"
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Artículos de revistas sobre el tema "Human gait model"
Otoda, Yuji, Hiroshi Kimura y Kunikatsu Takase. "Construction of Gait Adaptation Model in Human Splitbelt Treadmill Walking". Applied Bionics and Biomechanics 6, n.º 3-4 (2009): 269–84. http://dx.doi.org/10.1155/2009/305061.
Texto completoBhangale, Ashish. "Human Gait Model for Automatic Extraction and Description for Gait Recognition". International Journal on Bioinformatics & Biosciences 2, n.º 2 (30 de junio de 2012): 15–28. http://dx.doi.org/10.5121/ijbb.2012.2202.
Texto completoDuan, X. H., R. H. Allen y J. Q. Sun. "A stiffness-varying model of human gait". Medical Engineering & Physics 19, n.º 6 (septiembre de 1997): 518–24. http://dx.doi.org/10.1016/s1350-4533(97)00022-2.
Texto completoAshkenazy, Yosef, Jeffrey M. Hausdorff, Plamen Ch. Ivanov y H. Eugene Stanley. "A stochastic model of human gait dynamics". Physica A: Statistical Mechanics and its Applications 316, n.º 1-4 (diciembre de 2002): 662–70. http://dx.doi.org/10.1016/s0378-4371(02)01453-x.
Texto completoAbdolvahab, Mohammad. "A synergetic model for human gait transitions". Physica A: Statistical Mechanics and its Applications 433 (septiembre de 2015): 74–83. http://dx.doi.org/10.1016/j.physa.2015.03.049.
Texto completoLacker, HM, TH Choi, S. Schenk, B. Gupta, RP Narcessian, SA Sisto, S. Massood et al. "21 A mathematical model of human gait dynamics". Gait & Posture 5, n.º 2 (abril de 1997): 176. http://dx.doi.org/10.1016/s0966-6362(97)83418-2.
Texto completoZeng, Wei, Cong Wang y Yuanqing Li. "Model-Based Human Gait Recognition Via Deterministic Learning". Cognitive Computation 6, n.º 2 (7 de junio de 2013): 218–29. http://dx.doi.org/10.1007/s12559-013-9221-4.
Texto completoAlsaif, Omar Ibrahim, Saba Qasim Hasan y Abdulrafa Hussain Maray. "Using skeleton model to recognize human gait gender". IAES International Journal of Artificial Intelligence (IJ-AI) 12, n.º 2 (1 de junio de 2023): 974. http://dx.doi.org/10.11591/ijai.v12.i2.pp974-983.
Texto completoYang, Fan, Jun Wang y Jin Ping Sun. "Human Gaits Differentiation Based on Micro-Doppler Features". Advanced Materials Research 846-847 (noviembre de 2013): 203–6. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.203.
Texto completoHUANG, BUFU, MENG CHEN, KA KEUNG LEE y YANGSHENG XU. "HUMAN IDENTIFICATION BASED ON GAIT MODELING". International Journal of Information Acquisition 04, n.º 01 (marzo de 2007): 27–38. http://dx.doi.org/10.1142/s0219878907001137.
Texto completoTesis sobre el tema "Human gait model"
Yoo, Jang-Hee. "Recognizing human gait by model-driven statistical analysis". Thesis, University of Southampton, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414595.
Texto completoNiu, Feng. "Human Activity Recognition and Pathological Gait Pattern Identification". Scholarly Repository, 2007. http://scholarlyrepository.miami.edu/oa_dissertations/247.
Texto completoSharif, Bidabadi Shiva. "Human Gait Model Development for Objective Analysis of Pre/Post Gait Characteristics Following Lumbar Spine Surgery". Thesis, Curtin University, 2019. http://hdl.handle.net/20.500.11937/78468.
Texto completoKo, Seung-uk. "Human gait analysis by gait pattern measurement and forward dynamic model combined with non linear feedback control /". Connect to this title online, 2007. http://hdl.handle.net/1957/3754.
Texto completoXiao, Ming. "Computer simulation of human walking model sensitivity and application to stroke gait /". Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 129 p, 2009. http://proquest.umi.com/pqdweb?did=1885693291&sid=2&Fmt=2&clientId=8331&RQT=309&VName=PQD.
Texto completoSrinivasan, Sujatha. "Low-dimensional modeling and analysis of human gait with application to the gait of transtibial prosthesis users". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1179865923.
Texto completoLane, Gregory. "Human Knee FEA Model for Transtibial Amputee Tibial Cartilage Pressure in Gait and Cycling". DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1833.
Texto completoBoonpratatong, Amaraporn. "Motion prediction and dynamic stability analysis of human walking : the effect of leg property". Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/motion-prediction-and-dynamic-stability-analysis-of-human-walking-the-effect-of-leg-property(f36922af-1231-4dac-a92f-a16cbed8d701).html.
Texto completoSmith, Benjamin A. "Model Free Human Pose Estimation with Application to the Classification of Abnormal Human Movement and the Detection of Hidden Loads". Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/28360.
Texto completoPh. D.
Hill, David Allen Ph D. Massachusetts Institute of Technology. "A 3D neuromuscular model of the human ankle-foot complex based on multi-joint biplanar fluoroscopy gait analysis". Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119073.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 111-117).
During the gait cycle, the human ankle complex serves as a primary power generator while simultaneously stabilizing the entire limb. These actions are controlled by an intricate interplay of several lower leg muscles that cannot be fully uncovered using experimental methods alone. A combination of experiments and mathematical modeling may be used to estimate aspects of neuromusculoskeletal functions that control human gait. In this research, a three-dimensional neuromuscular model of the human ankle-foot complex based on biplanar fluoroscopy gait analysis is presented. Biplanar fluoroscopy (BiFlo) enables three-dimensional bone kinematics analysis using x-ray videos and bone geometry from segmented CT. Hindered by a small capture volume relative to traditional optical motion capture (MOCAP), BiFlo applications to human movement are generally limited to single-joint motions with constrained range. Here, a hybrid procedure is developed for multi-joint gait analysis using BiFlo and MOCAP in tandem. MOCAP effectively extends BiFlo's field-of-view. Subjects walked at a self-selected pace along a level walkway while BiFlo, MOCAP, and ground reaction forces were collected. A novel methodology was developed to register separate BiFlo measurements of the knee and ankle-foot complex. Kinematic analysis of bones surrounding the knee, ankle, and foot was performed. Kinematics obtained using this technique were compared to those calculated using only MOCAP during stance phase. Results show that this hybrid protocol effectively measures knee and ankle kinematics in all three body planes. Additionally, sagittal plane kinematics for select foot bone segments (proximal phalanges, metatarsals, and midfoot) was realized. The proposed procedure offers a novel approach to human gait analysis that eliminates errors originated by soft tissue artifacts, and is especially useful for ankle joint analysis, whose complexities are often simplified in MOCAP studies. Outcomes of the BiFlo walking experiments helped guide the development of a three-dimensional neuromuscular model of the human ankle-foot complex. Driven by kinematics, kinetics, and electromyography (EMG), the model seeks to solve the redundancy problem, individual muscle-tendon contributions to net joint torque, in ankle and subtalar joint actuation during overground gait. Kinematics and kinetics from BiFlo walking trials enable estimations of muscle-tendon lengths, moment arms, and joint torques. EMG yields estimates of muscle activation. Using each of these as inputs, an optimization approach was employed to calculate sets of morphological parameters that simultaneously maximize the neuromuscular model's metabolic efficiency and fit to experimental joint torques. This approach is based on the hypothesis that the muscle-tendon morphology of the human leg has evolved to maximize metabolic efficiency of walking at self-selected speed. Optimal morphological parameter sets produce estimates of force contributions and states for individual muscles. This research lends insight into the possible roles of individual muscle-tendons in the leg that lead to efficient gait.
by David Allen Hill.
Ph. D.
Libros sobre el tema "Human gait model"
Van Den Meerssche, Dimitri. The World Bank's Lawyers. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192846495.001.0001.
Texto completoBauer, Jack. The Transformative Self. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780199970742.001.0001.
Texto completoButton, Chris, Ludovic Seifert, Jia Yi Chow, Duarte Araújo y Keith Davids. Dynamics of Skill Acquisition. 2a ed. Human Kinetics, 2021. http://dx.doi.org/10.5040/9781718214125.
Texto completoKokas, Aynne. Trafficking Data. Oxford University PressNew York, 2022. http://dx.doi.org/10.1093/oso/9780197620502.001.0001.
Texto completoKennedy, J. Gerald y Scott Peeples, eds. The Oxford Handbook of Edgar Allan Poe. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190641870.001.0001.
Texto completoFarias, Pedro Lima Gondim de y Marcus Aurélio de Freitas Barros. Advocacia na Era Digital: Uma análise sobre possíveis impactos práticos e jurídicos das novas tecnologias na dinâmica da advocacia privada. Brazil Publishing, 2021. http://dx.doi.org/10.31012/978-65-5861-213-1.
Texto completoCappuccio, Massimiliano L., ed. Handbook of Embodied Cognition and Sport Psychology. The MIT Press, 2019. http://dx.doi.org/10.7551/mitpress/10764.001.0001.
Texto completoShengelia, Revaz. Modern Economics. Universal, Georgia, 2021. http://dx.doi.org/10.36962/rsme012021.
Texto completoCapítulos de libros sobre el tema "Human gait model"
Nixon, Mark S., Tieniu Tan y Rama Chellappa. "Model-Based Approaches". En Human Identification Based on Gait, 107–33. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/978-0-387-29488-9_6.
Texto completoYang, Jiankun, Dewen Jin, Linhong Ji, Jichuan Zhang, Rencheng Wang, Xin Fang y Dawei Zhou. "An Inverse Dynamical Model for Slip Gait". En Digital Human Modeling, 253–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73321-8_30.
Texto completoBaker, Richard, Fabien Leboeuf, Julie Reay y Morgan Sangeux. "The Conventional Gait Model - Success and Limitations". En Handbook of Human Motion, 489–508. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-14418-4_25.
Texto completoBaker, Richard, Fabien Leboeuf, Julie Reay y Morgan Sangeux. "The Conventional Gait Model - Success and Limitations". En Handbook of Human Motion, 1–19. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-30808-1_25-2.
Texto completoYagi, Yasushi, Ikuhisa Mitsugami, Satoshi Shioiri y Hitoshi Habe. "Behavior Understanding Based on Intention-Gait Model". En Human-Harmonized Information Technology, Volume 2, 139–72. Tokyo: Springer Japan, 2017. http://dx.doi.org/10.1007/978-4-431-56535-2_5.
Texto completoBhanu, Bir y Ju Han. "Discrimination Analysis for Model-Based Gait Recognition". En Human Recognition at a Distance in Video, 57–64. London: Springer London, 2010. http://dx.doi.org/10.1007/978-0-85729-124-0_4.
Texto completoCalow, Roman, Bernd Michaelis y Ayoub Al-Hamadi. "Solutions for Model-Based Analysis of Human Gait". En Lecture Notes in Computer Science, 540–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45243-0_69.
Texto completoBhanu, Bir y Ju Han. "Model-Free Gait-Based Human Recognition in Video". En Human Recognition at a Distance in Video, 25–56. London: Springer London, 2010. http://dx.doi.org/10.1007/978-0-85729-124-0_3.
Texto completoBhanu, Bir y Ju Han. "Model-Based Human Recognition—2D and 3D Gait". En Human Recognition at a Distance in Video, 65–94. London: Springer London, 2010. http://dx.doi.org/10.1007/978-0-85729-124-0_5.
Texto completoZell, Petrissa y Bodo Rosenhahn. "A Physics-Based Statistical Model for Human Gait Analysis". En Lecture Notes in Computer Science, 169–80. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24947-6_14.
Texto completoActas de conferencias sobre el tema "Human gait model"
Shirke, Suvarna, S.S.Pawar y Kamal Shah. "Literature Review: Model Free Human Gait Recognition". En 2014 International Conference on Communication Systems and Network Technologies (CSNT). IEEE, 2014. http://dx.doi.org/10.1109/csnt.2014.252.
Texto completoSivolobov, Sergey. "Human Gait Model Optimization for Person Identification". En 2022 4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2022. http://dx.doi.org/10.1109/summa57301.2022.9973857.
Texto completoRani, Veenu y Munish Kumar. "DeepNet-Gait: Human Identification by Gait Using Convolutional Neural Network Model". En 2023 10th International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2023. http://dx.doi.org/10.1109/spin57001.2023.10117067.
Texto completoGeisheimer, Jonathan L., Eugene F. Greneker III y William S. Marshall. "High-resolution Doppler model of the human gait". En AeroSense 2002, editado por Nickolas L. Faust, James L. Kurtz y Robert Trebits. SPIE, 2002. http://dx.doi.org/10.1117/12.488286.
Texto completoLiu, Hongcheng, Xiaodong Zhang, Ke Zhu y Hang Niu. "Thigh Skin Strain Model for Human Gait Movement". En 2021 IEEE Asia Conference on Information Engineering (ACIE). IEEE, 2021. http://dx.doi.org/10.1109/acie51979.2021.9381089.
Texto completoLi, Zhihui y Fenggang Huang. "Human Gait Tracking Based on Linear Model Fitting". En 2006 International Multi-Symposiums on Computer and Computational Sciences (IMSCCS). IEEE, 2006. http://dx.doi.org/10.1109/imsccs.2006.76.
Texto completoGhaeminia, Mohammad H., Ali Badiezadeh y Shahriar B. Shokouhi. "An Efficient Energy Model for Human Gait Recognition". En 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2016. http://dx.doi.org/10.1109/dicta.2016.7797006.
Texto completoChen, Meng, Bufu Huang y Yangsheng Xu. "Human Abnormal Gait Modeling via Hidden Markov Model". En 2007 International Conference on Information Acquisition. IEEE, 2007. http://dx.doi.org/10.1109/icia.2007.4295787.
Texto completoDao, Trung-Kien. "A Human Gait Model Using Graph-Theoretic Method". En Proceedings of The 3rd IFToMM International Symposium on Robotics and Mechatronics, Chair Van-Hiep Dao. Singapore: Research Publishing Services, 2013. http://dx.doi.org/10.3850/978-981-07-7744-9_012.
Texto completoThayer, Jessica B. y Philip A. Voglewede. "Improvement of a Forward Dynamic Predictive Human Gait Model". En ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97162.
Texto completoInformes sobre el tema "Human gait model"
Muelaner, Jody, ed. Unsettled Issues in Commercial Vehicle Platooning. SAE International, noviembre de 2021. http://dx.doi.org/10.4271/epr2021027.
Texto completoCONSENSUS STUDY ON THE STATE OF THE HUMANITIES IN SOUTH AFRICA: STATUS, PROSPECTS AND STRATEGIES. Academy of Science of South Africa, 2011. http://dx.doi.org/10.17159/assaf.2016/0025.
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