{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T02:56:24Z","timestamp":1780368984481,"version":"3.54.1"},"reference-count":35,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2019,10,27]],"date-time":"2019-10-27T00:00:00Z","timestamp":1572134400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2018CDXYJX0019"],"award-info":[{"award-number":["2018CDXYJX0019"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2018CDGFJX0022"],"award-info":[{"award-number":["2018CDGFJX0022"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2019CDCGJX219"],"award-info":[{"award-number":["2019CDCGJX219"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["50975230"],"award-info":[{"award-number":["50975230"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013286","name":"Research Fund for the Doctoral Program of Higher Education of China","doi-asserted-by":"publisher","award":["20136102130001"],"award-info":[{"award-number":["20136102130001"]}],"id":[{"id":"10.13039\/501100013286","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CNGC Joint Funding Project","award":["6141B012814"],"award-info":[{"award-number":["6141B012814"]}]},{"name":"Foundation for Sci &amp; Tech Research Project of Chongqing Science &amp; Technology Bureau","award":["cstc2016jcyjA0472"],"award-info":[{"award-number":["cstc2016jcyjA0472"]}]},{"name":"Foundation for Sci &amp; Tech Research Project of Chongqing Science &amp; Technology Bureau","award":["cstc2017zdcy-zdzxX0007"],"award-info":[{"award-number":["cstc2017zdcy-zdzxX0007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To improve the multi-speed adaptability of the powered prosthetic knee, this paper presented a speed-adaptive neural network control based on a powered geared five-bar (GFB) prosthetic knee. The GFB prosthetic knee is actuated via a cylindrical cam-based nonlinear series elastic actuator that can provide the desired actuation for level-ground walking, and its attitude measurement is realized by two inertial sensors and one load cell on the prosthetic knee. To improve the performance of the control system, the motor control and the attitude measurement of the GFB prosthetic knee are run in parallel. The BP neural network uses input data from only the GFB prosthetic knee, and is trained by natural and artificially modified various gait patterns of different able-bodied subjects. To realize the speed-adaptive control, the prosthetic knee speed and gait cycle percentage are identified by the Gaussian mixture model-based gait classifier. Specific knee motion control instructions are generated by matching the neural network predicted gait percentage with the ideal walking gait. Habitual and variable speed level-ground walking experiments are conducted via an able-bodied subject, and the experimental results show that the neural network control system can handle both self-selected walking and variable speed walking with high adaptability.<\/jats:p>","DOI":"10.3390\/s19214662","type":"journal-article","created":{"date-parts":[[2019,10,28]],"date-time":"2019-10-28T04:44:31Z","timestamp":1572237871000},"page":"4662","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Design and Speed-Adaptive Control of a Powered Geared Five-Bar Prosthetic Knee Using BP Neural Network Gait Recognition"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0054-1053","authenticated-orcid":false,"given":"Yuanxi","family":"Sun","sequence":"first","affiliation":[{"name":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7046-8256","authenticated-orcid":false,"given":"Dianbiao","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Department of Mechanical Engineering, Vrije Universiteit Brussel, 1050 Brussels, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohong","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9410-5107","authenticated-orcid":false,"given":"Long","family":"Bai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjie","family":"Ge","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2215","DOI":"10.1109\/TNNLS.2016.2584559","article-title":"A New Powered Lower Limb Prosthesis Control Framework Based on Adaptive Dynamic Programming","volume":"28","author":"Wen","year":"2016","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2355","DOI":"10.1109\/TNSRE.2017.2744987","article-title":"Bio-Inspired Adaptive Control for Active Knee Exoprosthetics","volume":"25","author":"Pagel","year":"2017","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5301","DOI":"10.3233\/JIFS-169813","article-title":"Design of robust fractional order fuzzy sliding mode PID controller for two link robotic manipulator system","volume":"35","author":"Kumar","year":"2018","journal-title":"J. Intell. Fuzzy Syst."},{"key":"ref_4","first-page":"148","article-title":"Recursive least squares for a manipulator which learns by demonstration","volume":"16","author":"Rubio","year":"2019","journal-title":"RIAI Revista Iberoamericana de Automatica e Informatica Industrial"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1109\/TNSRE.2010.2087360","article-title":"Upslope walking with a powered knee and ankle prosthesis: Initial results with an amputee subject","volume":"19","author":"Sup","year":"2011","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2704","DOI":"10.1109\/TBME.2018.2813999","article-title":"Inertial Sensing for Gait Event Detection and Transfemoral Prosthesis Control Strategy","volume":"65","author":"Ledoux","year":"2018","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1007\/s10439-015-1464-7","article-title":"A Cyber Expert System for Auto-Tuning Powered Prosthesis Impedance Control Parameters","volume":"44","author":"Huang","year":"2016","journal-title":"Ann. Biomed. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/j.robot.2009.02.002","article-title":"Development of Adaptive Modular Active Leg (AMAL) using bipedal robotics technology","volume":"57","author":"Nandi","year":"2009","journal-title":"Robot. Auton. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1542","DOI":"10.1001\/jama.2011.465","article-title":"Real-time myoelectric control of knee and ankle motions for transfemoral amputees","volume":"305","author":"Hargrove","year":"2011","journal-title":"JAMA J. Am. Med. Assoc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1109\/TII.2011.2166770","article-title":"On Design and Implementation of Neural-Machine Interface for Artificial Legs","volume":"8","author":"Zhang","year":"2012","journal-title":"IEEE Tran. Ind. Inform."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1109\/86.830951","article-title":"Feedback error learning neural network for trans-femoral prosthesis","volume":"8","author":"Kalanovic","year":"2000","journal-title":"IEEE Tran. Rehabil. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1016\/j.asoc.2017.04.056","article-title":"Discrete time control based in neural networks for pendulums","volume":"68","author":"Rubio","year":"2017","journal-title":"Appl. Soft Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2216","DOI":"10.1049\/iet-cta.2011.0322","article-title":"Modified optimal control with a backpropagation network for robotic arms","volume":"6","author":"Rubio","year":"2012","journal-title":"IET Control Theory A"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Tileylioglu, E., and Yilmaz, A. (2015, January 25\u201329). Application of neural based estimation algorithm for gait phases of above knee prosthesis. Proceedings of the International Conference of the IEEE Engineering in Medicine & Biology Society, Milano, Italy.","DOI":"10.1109\/EMBC.2015.7319472"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1518","DOI":"10.1109\/TNSRE.2016.2639527","article-title":"Continuous Estimation of Human Multi-Joint Angles From sEMG Using a State-Space Model","volume":"25","author":"Ding","year":"2017","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_16","unstructured":"Zhao, H., Reher, J., Horn, J., and Paredes, V. (2015, January 11\u201314). Realization of stair ascent and motion transitions on prostheses utilizing optimization-based control and intent recognition. Proceedings of the IEEE International Conference on Rehabilitation Robotics, Singapore."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Li, S., He, L., Liu, S., Zhang, Y., and Yu, H. (2017, January 20\u201322). Recognition of locomotion patterns based on BP neural network during different walking speeds. Proceedings of the 2017 Chinese Automation Congress (CAC), Jinan, China.","DOI":"10.1109\/CAC.2017.8243706"},{"key":"ref_18","unstructured":"Liu, L., Yang, P., Liu, Z., Geng, Y., and Zhang, J. (2013, January 25\u201327). Leg amputees motion pattern recognition based on principal component analysis and BP network. Proceedings of the 25th ChineseControl and Decision Conference (CCDC), Guiyang, China."},{"key":"ref_19","first-page":"365","article-title":"ANN-based EMG classification for myoelectric control","volume":"6","author":"Oweis","year":"2014","journal-title":"Int. J. Med. Inform."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1109\/JAS.2017.7510619","article-title":"Intent pattern recognition of lower-limb motion based on mechanical sensors","volume":"4","author":"Liu","year":"2017","journal-title":"IEEE\/CAA J. Autom. Sinica"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"056021","DOI":"10.1088\/1741-2560\/11\/5\/056021","article-title":"Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses","volume":"11","author":"Young","year":"2014","journal-title":"J. Neural Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2016\/7984157","article-title":"Detection of Gait Modes Using an Artificial Neural Network during Walking with a Powered Ankle-Foot Orthosis","volume":"2016","author":"Islam","year":"2016","journal-title":"J. Biophys."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1109\/TNSRE.2016.2521686","article-title":"Swing Phase Control of Semi-Active Prosthetic Knee using Neural Network Predictive Control with Particle Swarm Optimization","volume":"24","author":"Ekkachai","year":"2016","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.bbe.2016.01.002","article-title":"Human impedance parameter estimation using artificial neural network for modelling physiotherapist motion","volume":"36","author":"Demir","year":"2016","journal-title":"Biocybern. Biomed. Eng."},{"key":"ref_25","unstructured":"Jung, J.Y., Chae, M.G., Jang, I.H., and Park, H. (November, January 30). A hybrid control method of an exoskeleton robot for intention-driven walking rehabilitation of stroke patients. Proceedings of the International Conference on Ubiquitous Robots and Ambient Intelligence, Jeju, Korea."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2627","DOI":"10.1109\/JSEN.2016.2515101","article-title":"The Lower Limbs Kinematics Analysis by Wearable Sensor Shoes","volume":"16","author":"Li","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_27","first-page":"99","article-title":"Study of circular cross correlation and phase lag to estimate knee angle: An application to prosthesis","volume":"1","author":"Joshi","year":"2010","journal-title":"Int. J. Biomech. Biomed. Robot."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1515\/bmt.2010.057","article-title":"Complementary limb motion estimation for the control of active knee prostheses","volume":"56","author":"Vallery","year":"2011","journal-title":"Biomed. Tech."},{"key":"ref_29","first-page":"57","article-title":"Prediction of lower extremities\u2019 movement by angle-angle diagrams and neural networks","volume":"13","author":"Kutilek","year":"2011","journal-title":"Acta Bioeng. Biomech."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1109\/TNSRE.2015.2401042","article-title":"Design and Evaluation of a Prosthetic Knee Joint Using the Geared Five-Bar Mechanism","volume":"23","author":"Sun","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s10439-013-0909-0","article-title":"Intent recognition in a powered lower limb prosthesis using time history information","volume":"42","author":"Young","year":"2014","journal-title":"Ann. Biomed. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.neucom.2011.05.033","article-title":"sEMG-based continuous estimation of joint angles of human legs by using BP neural network","volume":"78","author":"Zhang","year":"2012","journal-title":"Neurocomputing"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"140846","DOI":"10.1109\/ACCESS.2019.2944206","article-title":"Optimal design of a nonlinear series elastic actuator for the prosthetic knee joint based on the conjugate cylindrical cam","volume":"7","author":"Sun","year":"2019","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1183","DOI":"10.1080\/0305215X.2016.1241877","article-title":"Optimization of actuating torques in multi-bar prosthetic joints with springs","volume":"49","author":"Sun","year":"2017","journal-title":"Eng. Optimiz."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"061002","DOI":"10.1115\/1.4033666","article-title":"Solving the Kinematics of the Planar Mechanism Using Data Structures of Assur Groups","volume":"8","author":"Sun","year":"2016","journal-title":"J. Mech. Robot."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/21\/4662\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:29:43Z","timestamp":1760189383000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/21\/4662"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,27]]},"references-count":35,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["s19214662"],"URL":"https:\/\/doi.org\/10.3390\/s19214662","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,27]]}}}