{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T16:33:19Z","timestamp":1781886799469,"version":"3.54.5"},"reference-count":34,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T00:00:00Z","timestamp":1714348800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LTGY24E050002"],"award-info":[{"award-number":["LTGY24E050002"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["52105037"],"award-info":[{"award-number":["52105037"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["U21A20122"],"award-info":[{"award-number":["U21A20122"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["EM2021120104"],"award-info":[{"award-number":["EM2021120104"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["LTGY24E050002"],"award-info":[{"award-number":["LTGY24E050002"]}],"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":["52105037"],"award-info":[{"award-number":["52105037"]}],"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":["U21A20122"],"award-info":[{"award-number":["U21A20122"]}],"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":["EM2021120104"],"award-info":[{"award-number":["EM2021120104"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Laboratory of E&amp;M of the Ministry of Education and Zhejiang University of Technology","award":["LTGY24E050002"],"award-info":[{"award-number":["LTGY24E050002"]}]},{"name":"Key Laboratory of E&amp;M of the Ministry of Education and Zhejiang University of Technology","award":["52105037"],"award-info":[{"award-number":["52105037"]}]},{"name":"Key Laboratory of E&amp;M of the Ministry of Education and Zhejiang University of Technology","award":["U21A20122"],"award-info":[{"award-number":["U21A20122"]}]},{"name":"Key Laboratory of E&amp;M of the Ministry of Education and Zhejiang University of Technology","award":["EM2021120104"],"award-info":[{"award-number":["EM2021120104"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper investigates a method for precise mapping of human arm movements using sEMG signals. A multi-channel approach captures the sEMG signals, which, combined with the accurately calculated joint angles from an Inertial Measurement Unit, allows for action recognition and mapping through deep learning algorithms. Firstly, signal acquisition and processing were carried out, which involved acquiring data from various movements (hand gestures, single-degree-of-freedom joint movements, and continuous joint actions) and sensor placement. Then, interference signals were filtered out through filters, and the signals were preprocessed using normalization and moving averages to obtain sEMG signals with obvious features. Additionally, this paper constructs a hybrid network model, combining Convolutional Neural Networks and Artificial Neural Networks, and employs a multi-feature fusion algorithm to enhance the accuracy of gesture recognition. Furthermore, a nonlinear fitting between sEMG signals and joint angles was established based on a backpropagation neural network, incorporating momentum term and adaptive learning rate adjustments. Finally, based on the gesture recognition and joint angle prediction model, prosthetic arm control experiments were conducted, achieving highly accurate arm movement prediction and execution. This paper not only validates the potential application of sEMG signals in the precise control of robotic arms but also lays a solid foundation for the development of more intuitive and responsive prostheses and assistive devices.<\/jats:p>","DOI":"10.3390\/s24092827","type":"journal-article","created":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T08:49:24Z","timestamp":1714380564000},"page":"2827","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Mapping Method of Human Arm Motion Based on Surface Electromyography Signals"],"prefix":"10.3390","volume":"24","author":[{"given":"Yuanyuan","family":"Zheng","sequence":"first","affiliation":[{"name":"School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"},{"name":"Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8532-4855","authenticated-orcid":false,"given":"Hanqi","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bochen","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6489-2330","authenticated-orcid":false,"given":"Peng","family":"Sun","sequence":"additional","affiliation":[{"name":"Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China"},{"name":"College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Feng, M., and Meunier, J. 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