{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T18:47:50Z","timestamp":1792090070945,"version":"4.4.0"},"reference-count":38,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T00:00:00Z","timestamp":1702857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61903255"],"award-info":[{"award-number":["61903255"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2020YFC2007902"],"award-info":[{"award-number":["2020YFC2007902"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China","award":["61903255"],"award-info":[{"award-number":["61903255"]}]},{"name":"National Key Research and Development Program of China","award":["2020YFC2007902"],"award-info":[{"award-number":["2020YFC2007902"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Exoskeleton rehabilitation robots have been widely used in the rehabilitation treatment of stroke patients. Clinical studies confirmed that rehabilitation training with active movement intentions could improve the effectiveness of rehabilitation treatment significantly. This research proposes a real-time control method for an upper limb exoskeleton based on the active torque prediction model. To fulfill the goal of individualized and precise rehabilitation, this method has an adjustable parameter assist ratio that can change the strength of the assist torque under the same conditions. In this study, upper limb muscles\u2019 EMG signals and elbow angle were chosen as the sources of control signals. The active torque prediction model was then trained using a BP neural network after appropriately extracting features. The model exhibited good accuracy on PC and embedded systems, according to the experimental results. In the embedded system, the RMSE of this model was 0.1956 N\u00b7m and 94.98%. In addition, the proposed real-time control system also had an extremely low delay of only 40 ms, which would significantly increase the adaptability of human\u2013computer interactions.<\/jats:p>","DOI":"10.3390\/bioengineering10121441","type":"journal-article","created":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T10:04:47Z","timestamp":1702893887000},"page":"1441","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["A Real-Time Control Method for Upper Limb Exoskeleton Based on Active Torque Prediction Model"],"prefix":"10.3390","volume":"10","author":[{"given":"Sujiao","family":"Li","sequence":"first","affiliation":[{"name":"Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China"},{"name":"Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, China"},{"name":"Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2683-1080","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China"},{"name":"Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0240-4004","authenticated-orcid":false,"given":"Qiaoling","family":"Meng","sequence":"additional","affiliation":[{"name":"Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China"},{"name":"Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, China"},{"name":"Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongliu","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China"},{"name":"Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, China"},{"name":"Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4284566","DOI":"10.1155\/2022\/4284566","article-title":"Prediction Model Construction for Ischemic Stroke Recurrence with BP Network and Multivariate Logistic Regression and Effect of Individualized Health Education","volume":"2022","author":"Lu","year":"2022","journal-title":"Comput. Math. Methods Med."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Gao, B., Wei, C., Ma, H., Yang, S., Ma, X., and Zhang, S. (2018). Real-Time Evaluation of the Signal Processing of sEMG Used in Limb Exoskeleton Rehabilitation System. Appl. Bionics Biomech., 2018.","DOI":"10.1155\/2018\/1391032"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Wang, P., Zhang, Q., Wang, Y., and Ru, F. (2017, January 5\u20138). Active Tracking Movements of Flexion and Extension on the Elbow Joint for an Initial Prototype of EMG-Driven Assistant Exoskeleton. Proceedings of the 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, China.","DOI":"10.1109\/ROBIO.2017.8324825"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1109\/TNSRE.2008.926707","article-title":"Assistive control system using continuous myoelectric signal in robot-aided arm training for patients after stroke","volume":"16","author":"Song","year":"2008","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1177\/23969873211061027","article-title":"The effect of motor relearning on balance, mobility and performance of activities of daily living among post-stroke patients: Study protocol for a randomised controlled trial","volume":"7","author":"Ghrouz","year":"2022","journal-title":"Eur. Stroke J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/s12984-016-0190-1","article-title":"Technology-assisted stroke rehabilitation in Mexico: A pilot randomized trial comparing traditional therapy to circuit training in a Robot\/technology-assisted therapy gym","volume":"13","author":"Montes","year":"2016","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1109\/TMRB.2020.3034497","article-title":"A Multi-Functional Lower- and Upper-Limb Stroke Rehabilitation Robot","volume":"2","author":"Mehrabi","year":"2020","journal-title":"IEEE Trans. Med. Robot. Bionics"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Uivarosan, D., Bungau, S.G., Nistor-Cseppento, C.D., Negru, P.A., Bungau, A.F., Sabau, A.M., Tit, D.M., Uivaraseanu, B., and Radu, A.F. (2022). Application of Robotic Recovery Techniques to Stroke Survivors-Bibliometric Analysis. J. Pers. Med., 12.","DOI":"10.3390\/jpm12122066"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Guo, S.X., Ding, Y.B., and Guo, J. (2021, January 8\u201311). Control of A Lower Limb Exoskeleton Robot by Upper Limb sEMG Signal. Proceedings of the 2021 IEEE International Conference on Mechatronics and Automation (ICMA), Takamatsu, Japan.","DOI":"10.1109\/ICMA52036.2021.9512775"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Qassim, H.M., and Wan Hasan, W.Z. (2020). A Review on Upper Limb Rehabilitation Robots. Appl. Sci., 10.","DOI":"10.3390\/app10196976"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/s10033-022-00749-6","article-title":"Development of a Wearable Upper Limb Rehabilitation Robot Based on Reinforced Soft Pneumatic Actuators","volume":"35","author":"Chen","year":"2022","journal-title":"Chin. J. Mech. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1089\/soro.2020.0090","article-title":"An Exoneuromusculoskeleton for Self-Help Upper Limb Rehabilitation After Stroke","volume":"9","author":"Nam","year":"2022","journal-title":"Soft Robot."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1097\/PRS.0000000000009208","article-title":"Surface Electromyography-Driven Therapeutic Gaming for Rehabilitation of Upper Extremity Weakness: A Pilot Study","volume":"150","author":"Liu","year":"2022","journal-title":"Plast. Reconstr. Surg."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ye, W., Yang, C., and Xie, Q. (2012, January 6\u20138). The development of an Exoskeleton Robot for Co-Manipulation of Human Upper Limb Movement. Proceedings of the 10th World Congress on Intelligent Control and Automation (WCICA 2012), Beijing, China.","DOI":"10.1109\/WCICA.2012.6359125"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Singh, R.M., Chatterji, S., and Kumar, A. (2013, January 21\u201323). A Review on Surface EMG based Control Schemes of Exoskeleton Robot in Stroke Rehabilitation. Proceedings of the 2013 International Conference on Machine Intelligence and Research Advancement (ICMIRA 2013), Katra, India.","DOI":"10.1109\/ICMIRA.2013.65"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yahya, Y.Z., and Al-Sawaff, Z.H. (2020). Design and modeling of an upper limb exoskeleton to assist elbow joint movement using surface emg signals. Biomed. Eng. Appl. Basis Commun., 32.","DOI":"10.4015\/S1016237220500064"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1142\/S0219519411003880","article-title":"Robot-assisted stroke rehabilitation: Joint torque\/force conversion from emg using ga process","volume":"11","author":"Parasuraman","year":"2011","journal-title":"J. Mech. Med. Biol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"224","DOI":"10.3389\/fneur.2020.00224","article-title":"Effects of Changes in Ankle Joint Angle on the Relation Between Plantarflexion Torque and EMG Magnitude in Major Plantar Flexors of Male Chronic Stroke Survivors","volume":"11","author":"Son","year":"2020","journal-title":"Front. Neurol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.bspc.2018.12.020","article-title":"An upper limb movement estimation from electromyography by using BP neural network","volume":"49","author":"Zhang","year":"2019","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Asokan, A., Vigneshwar, M., and IEEE (2019, January 9\u201311). Design and Control of an EMG-based Low-cost Exoskeleton for Stroke Rehabilitation. Proceedings of the 2019 5th Indian Control Conference (ICC), New Delhi, India.","DOI":"10.1109\/INDIANCC.2019.8715555"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1109\/LRA.2020.3043197","article-title":"Development of an Intention-Based Adaptive Neural Cooperative Control Strategy for Upper-Limb Robotic Rehabilitation","volume":"6","author":"Wu","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1080\/10749357.2021.1943797","article-title":"A scoping review of design requirements for a home-based upper limb rehabilitation robot for stroke","volume":"29","author":"Li","year":"2022","journal-title":"Top. Stroke Rehabil."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Chen, X., Zhang, X., Zhao, Z.Y., Yang, J.H., Lantz, V., and Wang, K.Q. (2007, January 11\u201313). Hand Gesture Recognition Research based on Surface EMG Sensors and 2D-Accelerometers. Proceedings of the 11th IEEE International Symposium on Wearable Computers, Boston, MA, USA.","DOI":"10.1109\/ISWC.2007.4373769"},{"key":"ref_24","unstructured":"(1988). Human Dimensions of Chinese Adults (Standard No. GB\/T 10000-1988)."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2051","DOI":"10.1007\/s11431-022-2145-x","article-title":"A review of the design of load-carrying exoskeletons","volume":"65","author":"Liang","year":"2022","journal-title":"Sci. China (Technol. Sci.)"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ma, Y., Xie, S.Q., and Zhang, Y. (2014, January 17\u201320). A Patient-Specific EMG-Driven Musculoskeletal Model for Improving the Effectiveness of Robotic Neurorehabilitation. Proceedings of the 7th International Conference on Intelligent Robotics and Applications (ICIRA), Guangzhou, China.","DOI":"10.1007\/978-3-319-13966-1_38"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.1109\/JBHI.2013.2286455","article-title":"sEMG-Based Joint Force Control for an Upper-Limb Power-Assist Exoskeleton Robot","volume":"18","author":"Li","year":"2014","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1109\/TSMCB.2012.2185843","article-title":"An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot","volume":"42","author":"Kiguchi","year":"2012","journal-title":"IEEE Trans. Syst. Man Cybern. Part B (Cybern.)"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1002\/pamm.201610009","article-title":"Fuzzy-Based Analysis of a Hill-Type Muscle Model","volume":"16","author":"Fehr","year":"2016","journal-title":"Proc. Appl. Math. Mech."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/0045-7825(88)90085-0","article-title":"A modified Lagrangian formulation for the dynamic analysis of constrained mechanical systems","volume":"71","author":"Bayo","year":"1988","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e00938","DOI":"10.1016\/j.heliyon.2018.e00938","article-title":"State-of-the-art in artificial neural network applications: A survey","volume":"4","author":"Abiodun","year":"2018","journal-title":"Heliyon"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1515\/CCLM.2010.045","article-title":"Artificial intelligence for diagnostic purposes: Principles, procedures and limitations","volume":"48","author":"Cleophas","year":"2010","journal-title":"Clin. Chem. Lab. Med."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1007\/s40684-020-00202-w","article-title":"Performance Analysis of Super Twisting Sliding Mode Controller by ADAMS-MATLAB Co-simulation in Lower Extremity Exoskeleton","volume":"7","author":"Nair","year":"2020","journal-title":"Int. J. Precis. Eng. Manuf. Green Technol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Tahamipour-Z, S.M., Kardan, I., Kalani, H., and Akbarzadeh, A. (2020, January 2\u20134). A PSO-MLPANN Hybrid Approach for Estimation of Human Joint Torques from sEMG Signals. Proceedings of the 2020 8th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS), Mashhad, Iran.","DOI":"10.1109\/CFIS49607.2020.9238724"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Huang, Y., Chen, K., Zhang, X., Wang, K., and Ota, J. (2020). Joint torque estimation for the human arm from sEMG using backpropagation neural networks and autoencoders. Biomed. Signal Process. Control., 62.","DOI":"10.1016\/j.bspc.2020.102051"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s11431-018-9354-5","article-title":"Bio-signal based elbow angle and torque simultaneous prediction during isokinetic contraction","volume":"62","author":"Zhou","year":"2019","journal-title":"Sci. China Technol. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Bueno, D.R., Montano, L., and IEEE (2013, January 3\u20137). Multijoint Upper Limb Torque Estimation from sEMG Measurements. Proceedings of the 2013 35th Annual International Conference of The IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan.","DOI":"10.1109\/EMBC.2013.6611227"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1650031","DOI":"10.1142\/S0219843616500316","article-title":"Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training","volume":"14","author":"Ye","year":"2017","journal-title":"Int. J. Humanoid Robot."}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/10\/12\/1441\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:41:02Z","timestamp":1760132462000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/10\/12\/1441"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,18]]},"references-count":38,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["bioengineering10121441"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering10121441","relation":{},"ISSN":["2306-5354"],"issn-type":[{"value":"2306-5354","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,18]]}}}