Artículos de revistas sobre el tema "SEMG-force model"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte los 44 mejores artículos de revistas para su investigación sobre el tema "SEMG-force model".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Explore artículos de revistas sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.
Hou, Wensheng, Xiaolin Zheng, Yingtao Jiang, Jun Zheng, Chenglin Peng y Rong Xu. "A STUDY OF MODELS FOR HANDGRIP FORCE PREDICTION FROM SURFACE ELECTROMYOGRAPHY OF EXTENSOR MUSCLE". Biomedical Engineering: Applications, Basis and Communications 21, n.º 02 (abril de 2009): 81–88. http://dx.doi.org/10.4015/s1016237209001131.
Texto completoGAO, YONGSHENG, SHENGXIN WANG, FEIYUN XIAO y JIE ZHAO. "AN ANGLE-EMG BIOMECHANICAL MODEL OF THE HUMAN ELBOW JOINT". Journal of Mechanics in Medicine and Biology 16, n.º 06 (septiembre de 2016): 1650078. http://dx.doi.org/10.1142/s0219519416500780.
Texto completoWang, Yuan, Fan Li, Haoting Liu, Zhiqiang Zhang, Duming Wang, Shanguang Chen, Chunhui Wang y Jinhui Lan. "Robust muscle force prediction using NMFSEMD denoising and FOS identification". PLOS ONE 17, n.º 8 (3 de agosto de 2022): e0272118. http://dx.doi.org/10.1371/journal.pone.0272118.
Texto completoKhoshdel, Vahab y Alireza Akbarzadeh. "An optimized artificial neural network for human-force estimation: consequences for rehabilitation robotics". Industrial Robot: An International Journal 45, n.º 3 (21 de mayo de 2018): 416–23. http://dx.doi.org/10.1108/ir-10-2017-0190.
Texto completoLv, Ying, Qingli Zheng, Xiubin Chen, Yi Jia, Chunsheng Hou y Meiwen An. "Analysis on Muscle Forces of Extrinsic Finger Flexors and Extensors in Flexor Movements with sEMG and Ultrasound". Mathematical Problems in Engineering 2022 (12 de mayo de 2022): 1–10. http://dx.doi.org/10.1155/2022/7894935.
Texto completoYANG, D. D., W. S. HOU, X. Y. WU, J. ZHENG, X. L. ZHENG, Y. T. JIANG y L. MA. "IMPACT OF FINGERTIP ACTIONS ON TOTAL POWER OF SURFACE ELECTROMYOGRAPHY FROM EXTRINSIC HAND MUSCLES". Journal of Mechanics in Medicine and Biology 12, n.º 03 (junio de 2012): 1250056. http://dx.doi.org/10.1142/s0219519411004800.
Texto completoWang, Kai, Xianmin Zhang, Jun Ota y Yanjiang Huang. "Development of an SEMG-Handgrip Force Model Based on Cross Model Selection". IEEE Sensors Journal 19, n.º 5 (1 de marzo de 2019): 1829–38. http://dx.doi.org/10.1109/jsen.2018.2883660.
Texto completoHou, Wensheng, Xiaoying Wu, Jun Zheng, Li Ma, Xiaolin Zheng, Yingtao Jiang, Dandan Yang, Shizhi Qian y Chenglin Peng. "CHARACTERIZATION OF FINGER ISOMETRIC FORCE PRODUCTION WITH MAXIMUM POWER OF SURFACE ELECTROMYOGRAPHY". Biomedical Engineering: Applications, Basis and Communications 21, n.º 03 (junio de 2009): 193–99. http://dx.doi.org/10.4015/s1016237209001258.
Texto completoMarklin, Richard W., Jonathon E. Slightam, Mark L. Nagurka, Casey D. Garces, Lovely Krishen y Eric H. Bauman. "New Pistol Grip Control for an Electric Utility Aerial Bucket Reduces Risk of Forearm Muscle Fatigue". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, n.º 1 (septiembre de 2018): 888–92. http://dx.doi.org/10.1177/1541931218621204.
Texto completoWang, Jinfeng, Muye Pang, Peixuan Yu, Biwei Tang, Kui Xiang y Zhaojie Ju. "Effect of Muscle Fatigue on Surface Electromyography-Based Hand Grasp Force Estimation". Applied Bionics and Biomechanics 2021 (15 de febrero de 2021): 1–12. http://dx.doi.org/10.1155/2021/8817480.
Texto completoCHEN, JIANGCHENG, XIAODONG ZHANG, LINXIA GU y CARL NELSON. "ESTIMATING MUSCLE FORCES AND KNEE JOINT TORQUE USING SURFACE ELECTROMYOGRAPHY: A MUSCULOSKELETAL BIOMECHANICAL MODEL". Journal of Mechanics in Medicine and Biology 17, n.º 04 (2 de marzo de 2017): 1750069. http://dx.doi.org/10.1142/s0219519417500695.
Texto completoDorgham, Osama, Ibrahim Al-Mherat, Jawdat Al-Shaer, Sulieman Bani-Ahmad y Stephen Laycock. "Smart System for Prediction of Accurate Surface Electromyography Signals Using an Artificial Neural Network". Future Internet 11, n.º 1 (21 de enero de 2019): 25. http://dx.doi.org/10.3390/fi11010025.
Texto completoFOO, Chee-Sheng, Takahiro KIKUCHI, Yukihiro MICHIWAKI, Takuji KOIKE y Takuya HASHIMOTO. "Muscle Force Estimation during Swallowing based on Musculoskeletal Model and sEMG Measurement". Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2017 (2017): 2P2—J03. http://dx.doi.org/10.1299/jsmermd.2017.2p2-j03.
Texto completoHasanzadeh Fereydooni, Rohollah, Hassan Siahkali, Heidar Ali Shayanfar y Amir Houshang Mazinan. "sEMG-based variable impedance control of lower-limb rehabilitation robot using wavelet neural network and model reference adaptive control". Industrial Robot: the international journal of robotics research and application 47, n.º 3 (16 de enero de 2020): 349–58. http://dx.doi.org/10.1108/ir-10-2019-0210.
Texto completoAli, W. y S. Kolyubin. "EMG-Based Grasping Force Estimation for Robot Skill Transfer Learning". Nelineinaya Dinamika 18, n.º 5 (2022): 0. http://dx.doi.org/10.20537/nd221221.
Texto completoMadden, Kaci E., Dragan Djurdjanovic y Ashish D. Deshpande. "Using a System-Based Monitoring Paradigm to Assess Fatigue during Submaximal Static Exercise of the Elbow Extensor Muscles". Sensors 21, n.º 4 (3 de febrero de 2021): 1024. http://dx.doi.org/10.3390/s21041024.
Texto completoCenit, Mikecon y Vaibhav Gandhi. "Design and development of the sEMG-based exoskeleton strength enhancer for the legs". Journal of Mechatronics, Electrical Power, and Vehicular Technology 10, n.º 2 (28 de noviembre de 2019): 61. http://dx.doi.org/10.14203/j.mev.2019.v10.61-71.
Texto completoCenit, Mikecon y Vaibhav Gandhi. "Design and development of the sEMG-based exoskeleton strength enhancer for the legs". Journal of Mechatronics, Electrical Power, and Vehicular Technology 11, n.º 2 (22 de diciembre de 2020): 64. http://dx.doi.org/10.14203/j.mev.2020.v11.64-74.
Texto completoKong, Dezhi, Wendong Wang, Dong Guo y Yikai Shi. "RBF Sliding Mode Control Method for an Upper Limb Rehabilitation Exoskeleton Based on Intent Recognition". Applied Sciences 12, n.º 10 (15 de mayo de 2022): 4993. http://dx.doi.org/10.3390/app12104993.
Texto completoIto, A., Y. Tamura y M. Saito. "Simulation of force in human elbow biceps by a motor system model using SEMG signal". Journal of Biomechanics 39 (enero de 2006): S494. http://dx.doi.org/10.1016/s0021-9290(06)85020-7.
Texto completoNa, Youngjin y Jung Kim. "Dynamic Elbow Flexion Force Estimation Through a Muscle Twitch Model and sEMG in a Fatigue Condition". IEEE Transactions on Neural Systems and Rehabilitation Engineering 25, n.º 9 (septiembre de 2017): 1431–39. http://dx.doi.org/10.1109/tnsre.2016.2628373.
Texto completoLu, Wei, Lifu Gao, Huibin Cao y Zebin Li. "sEMG-Upper Limb Interaction Force Estimation Framework Based on Residual Network and Bidirectional Long Short-Term Memory Network". Applied Sciences 12, n.º 17 (29 de agosto de 2022): 8652. http://dx.doi.org/10.3390/app12178652.
Texto completoLi, Zebin, Lifu Gao, Wei Lu, Daqing Wang, Huibin Cao y Gang Zhang. "Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS-SVR". Sensors 22, n.º 12 (20 de junio de 2022): 4651. http://dx.doi.org/10.3390/s22124651.
Texto completoLi, Bo, Bo Yuan, Shuai Tang, Yuwen Mao, Dongmei Zhang, Changyun Huang y Bilian Tan. "Biomechanical design analysis and experiments evaluation of a passive knee-assisting exoskeleton for weight-climbing". Industrial Robot: An International Journal 45, n.º 4 (18 de junio de 2018): 436–45. http://dx.doi.org/10.1108/ir-11-2017-0207.
Texto completoWilcox, M., H. Brown, K. Johnson, M. Sinisi y T. J. Quick. "An assessment of fatigability following nerve transfer to reinnervate elbow flexor muscles". Bone & Joint Journal 101-B, n.º 7 (julio de 2019): 867–71. http://dx.doi.org/10.1302/0301-620x.101b7.bjj-2019-0005.r1.
Texto completoAdeola-Bello, Zulikha Ayomikun y Norsinnira Zainul Azlan. "Power Assist Rehabilitation Robot and Motion Intention Estimation". International Journal of Robotics and Control Systems 2, n.º 2 (14 de mayo de 2022): 297–316. http://dx.doi.org/10.31763/ijrcs.v2i2.650.
Texto completoHe, Ruihua, Xinyu Sun, Xuedou Yu, Hongtao Xia y Shuaijie Chen. "Static Model of Athlete’s Upper Limb Posture Rehabilitation Training Indexes". BioMed Research International 2022 (18 de julio de 2022): 1–9. http://dx.doi.org/10.1155/2022/9353436.
Texto completoXu, Lingfeng, Xiang Chen, Shuai Cao, Xu Zhang y Xun Chen. "Feasibility Study of Advanced Neural Networks Applied to sEMG-Based Force Estimation". Sensors 18, n.º 10 (25 de septiembre de 2018): 3226. http://dx.doi.org/10.3390/s18103226.
Texto completoYokoyama, Masayuki, Ryohei Koyama y Masao Yanagisawa. "An Evaluation of Hand-Force Prediction Using Artificial Neural-Network Regression Models of Surface EMG Signals for Handwear Devices". Journal of Sensors 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/3980906.
Texto completoSheahan, Peter J., Joshua G. A. Cashaback y Steven L. Fischer. "Evaluating the Ergonomic Benefit of a Wrist Brace on Wrist Posture, Muscle Activity, Rotational Stiffness, and Peak Shovel-Ground Impact Force During a Simulated Tree-Planting Task". Human Factors: The Journal of the Human Factors and Ergonomics Society 59, n.º 6 (9 de mayo de 2017): 911–24. http://dx.doi.org/10.1177/0018720817708084.
Texto completoWang, Mengcheng, Chuan Zhao, Alan Barr, Suihuai Yu, Jay Kapellusch y Carisa Harris Adamson. "Hand Posture and Force Estimation using Surface Electromyography and an Artificial Neural Network". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, n.º 1 (diciembre de 2020): 1247–48. http://dx.doi.org/10.1177/1071181320641296.
Texto completoLow, Kin Huat, Shuxiang Guo, Xinyan Deng, Ravi Vaidyanathan, James Tangorra, Hoon Cheol Park y Fumiya Iida. "Special Issue on Focused Areas and Future Trends of Bio-Inspired Robots “Analysis, Control, and Design for Bio-Inspired Robotics”". Journal of Robotics and Mechatronics 24, n.º 4 (20 de agosto de 2012): 559–60. http://dx.doi.org/10.20965/jrm.2012.p0559.
Texto completoMokri, Chiako, Mahdi Bamdad y Vahid Abolghasemi. "Muscle force estimation from lower limb EMG signals using novel optimised machine learning techniques". Medical & Biological Engineering & Computing 60, n.º 3 (14 de enero de 2022): 683–99. http://dx.doi.org/10.1007/s11517-021-02466-z.
Texto completoPotluri, Chandrasekhar, Madhavi Anugolu, Marco P. Schoen, D. Subbaram Naidu, Alex Urfer y Steve Chiu. "Hybrid fusion of linear, non-linear and spectral models for the dynamic modeling of sEMG and skeletal muscle force: An application to upper extremity amputation". Computers in Biology and Medicine 43, n.º 11 (noviembre de 2013): 1815–26. http://dx.doi.org/10.1016/j.compbiomed.2013.08.023.
Texto completoLu, Wei, Lifu Gao, Huibin Cao, Zebin Li y Daqing Wang. "A comparison of contributions of individual muscle and combination muscles to interaction force prediction using KPCA-DRSN model". Frontiers in Bioengineering and Biotechnology 10 (7 de septiembre de 2022). http://dx.doi.org/10.3389/fbioe.2022.970859.
Texto completoShirzadi, Mehdi, Hamid Reza Marateb, Mónica Rojas-Martínez, Marjan Mansourian, Alberto Botter, Fabio Vieira dos Anjos, Taian Martins Vieira y Miguel Angel Mañanas. "A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs". Frontiers in Physiology 14 (27 de febrero de 2023). http://dx.doi.org/10.3389/fphys.2023.1098225.
Texto completoZhang, Qiang, Natalie Fragnito, Jason R. Franz y Nitin Sharma. "Fused ultrasound and electromyography-driven neuromuscular model to improve plantarflexion moment prediction across walking speeds". Journal of NeuroEngineering and Rehabilitation 19, n.º 1 (9 de agosto de 2022). http://dx.doi.org/10.1186/s12984-022-01061-z.
Texto completoHua, Shaoyang, Congqing Wang y Xuewei Wu. "A novel sEMG-based force estimation method using deep-learning algorithm". Complex & Intelligent Systems, 23 de abril de 2021. http://dx.doi.org/10.1007/s40747-021-00338-5.
Texto completoNarayanan, Sidharth y Venugopal Gopinath. "Generation and analysis of synthetic surface electromyography signals under varied muscle fiber type proportions and validation using recorded signals". Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 18 de enero de 2023, 095441192211492. http://dx.doi.org/10.1177/09544119221149234.
Texto completoChandrapal, Mervin, XiaoQi Chen, WenHui Wang, Benjamin Stanke y Nicolas Le Pape. "Investigating improvements to neural network based EMG to joint torque estimation". Paladyn, Journal of Behavioral Robotics 2, n.º 4 (1 de enero de 2011). http://dx.doi.org/10.2478/s13230-012-0007-2.
Texto completoWAN, LISHUANG, FAHAD ABDULLAH ALQURASHI y WOO-JIN JUNG. "PRACTICE AND DEVELOPMENT OF SPORTS SOMATIC SCIENCE IN SOCIAL PHYSICAL EDUCATION TEACHING USING FRACTAL THEORY". Fractals 30, n.º 02 (14 de febrero de 2022). http://dx.doi.org/10.1142/s0218348x22400886.
Texto completoShi, Lei, Zhen Liua y Chao Zhang. "A Control Framework of Lower Extremity Rehabilitation Exoskeleton based on Neuro-Muscular-Skeletal Model". Journal of Applied Information Science 3, n.º 1 (2015). http://dx.doi.org/10.21863/jais/2015.3.1.002.
Texto completoMao, He, Peng Fang, Yue Zheng, Lan Tian, Xiangxin Li, Pu Wang, Liang Peng y Guanglin Li. "Continuous grip force estimation from surface electromyography using generalized regression neural network". Technology and Health Care, 8 de septiembre de 2022, 1–15. http://dx.doi.org/10.3233/thc-220283.
Texto completoWang, Mengcheng, Chuan Zhao, Alan Barr, Hao Fan, Suihuai Yu, Jay Kapellusch y Carisa Harris Adamson. "Hand Posture and Force Estimation Using Surface Electromyography and an Artificial Neural Network". Human Factors: The Journal of the Human Factors and Ergonomics Society, 18 de mayo de 2021, 001872082110166. http://dx.doi.org/10.1177/00187208211016695.
Texto completo