{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:27:29Z","timestamp":1787012849930,"version":"build-2736575974"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Bavarian Ministry of Economic Affairs"},{"name":"Regional Development and Energy","award":["MV-2303-0006"],"award-info":[{"award-number":["MV-2303-0006"]}]},{"DOI":"10.13039\/501100000781","name":"European Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"name":"GRASPAGAIN","award":["101118089"],"award-info":[{"award-number":["101118089"]}]},{"name":"German Federal Ministry of Education and Research"},{"name":"MYOREHAB","award":["01DN23002"],"award-info":[{"award-number":["01DN23002"]}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Biomed. Eng."],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/tbme.2024.3432800","type":"journal-article","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T14:23:08Z","timestamp":1721830988000},"page":"3556-3568","source":"Crossref","is-referenced-by-count":16,"title":["Learning a Hand Model From Dynamic Movements Using High-Density EMG and Convolutional Neural Networks"],"prefix":"10.1109","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0455-0168","authenticated-orcid":false,"given":"Raul C.","family":"S\u00eempetru","sequence":"first","affiliation":[{"name":"Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2473-5816","authenticated-orcid":false,"given":"Andreas","family":"Arkudas","sequence":"additional","affiliation":[{"name":"Department of Plastic and Handsurgery, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7904-3166","authenticated-orcid":false,"given":"Dominik I.","family":"Braun","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8053-8575","authenticated-orcid":false,"given":"Marius","family":"Osswald","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0320-7421","authenticated-orcid":false,"given":"Daniela Souza","family":"de Oliveira","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0417-0336","authenticated-orcid":false,"given":"Bjoern","family":"Eskofier","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4888-543X","authenticated-orcid":false,"given":"Thomas M.","family":"Kinfe","sequence":"additional","affiliation":[{"name":"Division of Functional Neurosurgery and Stereotaxy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7118-5554","authenticated-orcid":false,"given":"Alessandro Del","family":"Vecchio","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.2011.217810"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3389\/fncom.2013.00023"},{"key":"ref3","first-page":"1","article-title":"Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands","volume-title":"Phys. Life Rev.","volume":"17","author":"Santello","year":"2016"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/abf186"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2022.3194104"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab0e2e"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/NER49283.2021.9441095"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2022.3153252"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2023.3252817"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.21105\/joss.00861"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC48229.2022.9870937"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2023.3295060"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ad3498"},{"issue":"9","key":"ref14","first-page":"1281","article-title":"DeepLabCut: Markerless pose estimation of user-defined body parts with deep learning","volume-title":"Nature Neurosci.","volume":"21","author":"Mathis","year":"2018"},{"issue":"13","key":"ref15","article-title":"Anipose: A toolkit for robust markerless 3 D pose estimation","volume-title":"Cell Rep.","volume":"36","author":"Karashchuk","year":"2021"},{"issue":"17","key":"ref16","article-title":"Data augmentation of surface electromyography for hand gesture recognition","volume-title":"Sensors","volume":"20","author":"Tsinganos","year":"2020"},{"key":"ref17","first-page":"112","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Paszke","year":"2019"},{"key":"ref18","article-title":"PyTorch lightning","author":"Falcon"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.00087"},{"key":"ref20","first-page":"1","article-title":"Decoupled weight decay regularization","author":"Loshchilov","year":"2018"},{"key":"ref21","first-page":"1","article-title":"On the convergence of adam and beyond","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Reddi","year":"2018"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1117\/12.2520589"},{"key":"ref23","volume-title":"Electromyography: Physiology, Engineering, and Noninvasive Applications","author":"Roberto","year":"2004"},{"issue":"5","key":"ref24","first-page":"359","article-title":"Multilayer feedforward networks are universal approximators","volume-title":"Neural Netw.","volume":"2","author":"Hornik","year":"1989"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00220.2021"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awae088"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2021.3057051"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ac823d"},{"key":"ref29","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.2009.178509"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1152\/japplphysiol.00482.2017"},{"key":"ref33","article-title":"Mechanical hand synergies during dynamic hand movements are mostly controlled in a non-synergistic way by spinal motor neurons","author":"Osswald","year":"2023"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-7793.1998.611bh.x"},{"key":"ref35","volume-title":"Gray\u2019s Anatomy","author":"Gray","year":"1878"},{"issue":"5","key":"ref36","first-page":"1617","article-title":"Developing RPC-Net: Leveraging high-density electromyography and machine learning for improved hand position estimation","volume-title":"IEEE Trans. Biomed. Eng.","volume":"71","author":"Rolandino","year":"2024"}],"container-title":["IEEE Transactions on Biomedical Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10\/10762826\/10607959.pdf?arnumber=10607959","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T22:52:44Z","timestamp":1735858364000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10607959\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":36,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tbme.2024.3432800","relation":{},"ISSN":["0018-9294","1558-2531"],"issn-type":[{"value":"0018-9294","type":"print"},{"value":"1558-2531","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}