{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T08:39:08Z","timestamp":1786523948981,"version":"build-2736575974"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U25A20144"],"award-info":[{"award-number":["U25A20144"]}],"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":["52525504"],"award-info":[{"award-number":["52525504"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1007\/s11517-026-03595-z","type":"journal-article","created":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T03:05:30Z","timestamp":1783134330000},"page":"2857-2867","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A novel SE-ResNet architecture for continuous estimation of wrist and hand movements from HD-sEMG"],"prefix":"10.1007","volume":"64","author":[{"given":"Lizhi","family":"Pan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8976-0374","authenticated-orcid":false,"given":"Zhe","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianmin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,4]]},"reference":[{"issue":"13","key":"3595_CR1","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1177\/0278364912459209","volume":"31","author":"M Grebenstein","year":"2012","unstructured":"Grebenstein M, Chalon M, Friedl W, Haddadin S, Wimb\u00f6ck T, Hirzinger G, Siegwart R (2012) The hand of the dlr hand arm system: Designed for interaction. Int J Robot Res 31(13):1531\u20131555","journal-title":"Int J Robot Res"},{"key":"3595_CR2","unstructured":"Reichel M (2004) Transformation of shadow dextrous hand and shadow finger test unit from prototype to product for intelligent manipulation and grasping. In: Intelligent manipulation and grasping, Inter Conf, Genova, Italy, vol 70"},{"issue":"3","key":"3595_CR3","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1109\/JBHI.2013.2249590","volume":"17","author":"AH Al-Timemy","year":"2013","unstructured":"Al-Timemy AH, Bugmann G, Escudero J, Outram N (2013) Classification of finger movements for the dexterous hand prosthesis control with surface electromyography. IEEE J Biomed Health Inform 17(3):608\u2013618","journal-title":"IEEE J Biomed Health Inform"},{"key":"3595_CR4","doi-asserted-by":"crossref","unstructured":"Massa B, Roccella S, Carrozza MC, Dario P (2002) Design and development of an underactuated prosthetic hand. In: Proceedings 2002 IEEE international conference on robotics and automation (Cat. No. 02CH37292), vol 4, pp 3374\u20133379","DOI":"10.1109\/ROBOT.2002.1014232"},{"issue":"5","key":"3595_CR5","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1177\/0278364909360852","volume":"29","author":"AM Dollar","year":"2010","unstructured":"Dollar AM, Howe RD (2010) The highly adaptive sdm hand: Design and performance evaluation. Int J Robot Res 29(5):585\u2013597","journal-title":"Int J Robot Res"},{"issue":"3","key":"3595_CR6","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1109\/TMECH.2002.802720","volume":"7","author":"H Kawasaki","year":"2002","unstructured":"Kawasaki H, Komatsu T, Uchiyama K (2002) Dexterous anthropomorphic robot hand with distributed tactile sensor: Gifu hand ii. IEEE\/ASME Trans Mechatron 7(3):296\u2013303","journal-title":"IEEE\/ASME Trans Mechatron"},{"key":"3595_CR7","doi-asserted-by":"publisher","first-page":"1283","DOI":"10.3389\/fphys.2019.01283","volume":"10","author":"A P\u00e9ter","year":"2019","unstructured":"P\u00e9ter A, Andersson E, Hegyi A, Finni T, Tarassova O, Cronin N, Grundstr\u00f6m H, Arndt A (2019) Comparing surface and fine-wire electromyography activity of lower leg muscles at different walking speeds. Front Physiol 10:1283","journal-title":"Front Physiol"},{"key":"3595_CR8","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1038\/s41597-023-02114-1","volume":"10","author":"JC Bradford","year":"2023","unstructured":"Bradford JC, Tweedell A, Leahy L (2023) High-density surface and intramuscular EMG data from the tibialis anterior during dynamic contractions. Scientific Data 10:434","journal-title":"Scientific Data"},{"issue":"2","key":"3595_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4172\/2168-9695.1000e107","volume":"1","author":"P Artemiadis","year":"2012","unstructured":"Artemiadis P (2012) Emg-based robot control interfaces: past, present and future. Adv Robot Autom 1(2):1\u20133","journal-title":"Adv Robot Autom"},{"issue":"5","key":"3595_CR10","first-page":"150","volume":"29","author":"J Ning","year":"2012","unstructured":"Ning J, Dosen S, Muller K, Farina D (2012) Myoelectric control of artificial limbs. IEEE Signal Process 29(5):150\u2013152","journal-title":"IEEE Signal Process"},{"issue":"5","key":"3595_CR11","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1109\/TBME.2016.2538296","volume":"63","author":"M Sartori","year":"2016","unstructured":"Sartori M, Lloyd DG, Farina D (2016) Neural data-driven musculoskeletal modeling for personalized neurorehabilitation technologies. IEEE Trans Biomed Eng 63(5):879\u2013893","journal-title":"IEEE Trans Biomed Eng"},{"key":"3595_CR12","doi-asserted-by":"publisher","first-page":"3999","DOI":"10.1109\/TNSRE.2023.3323347","volume":"31","author":"J Li","year":"2023","unstructured":"Li J, Yue S, Pan L (2023) Simultaneous and proportional control of wrist and hand movements based on a neural-driven musculoskeletal model. IEEE Trans Neural Syst Rehabil Eng 31:3999\u20134007","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"issue":"6","key":"3595_CR13","doi-asserted-by":"publisher","first-page":"1198","DOI":"10.1109\/TNSRE.2014.2323576","volume":"22","author":"A Ameri","year":"2014","unstructured":"Ameri A, Kamavuako EN, Scheme EJ, Englehart KB, Parker PA (2014) Support vector regression for improved real-time, simultaneous myoelectric control. IEEE Trans Neural Syst Rehabil Eng 22(6):1198\u20131209","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"issue":"2","key":"3595_CR14","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1109\/TNSRE.2014.2305520","volume":"22","author":"JM Hahne","year":"2014","unstructured":"Hahne JM, Biessmann F, Jiang N, Rehbaum H, Farina D, Meinecke FC, M\u00fcller K-R, Parra LC (2014) Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control. IEEE Trans Neural Syst Rehabil Eng 22(2):269\u2013279","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"issue":"3","key":"3595_CR15","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1109\/TNSRE.2013.2278411","volume":"22","author":"N Jiang","year":"2013","unstructured":"Jiang N, Rehbaum H, Vujaklija I, Graimann B, Farina D (2013) Intuitive, online, simultaneous, and proportional myoelectric control over two degrees-of-freedom in upper limb amputees. IEEE Trans Neural Syst Rehabil Eng 22(3):501\u2013510","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"issue":"6","key":"3595_CR16","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2017) ImageNet classification with Deep convolutional neural networks. Commun ACM 60(6):84\u201390","journal-title":"Commun ACM"},{"key":"3595_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.106126","volume":"122","author":"A Parvaiz","year":"2023","unstructured":"Parvaiz A, Khalid MA, Zafar R, Ameer H, Ali M, Fraz MM (2023) Vision transformers in medical computer vision \u2013 a contemplative retrospection. Eng Appl Artif Intell 122:106126","journal-title":"Eng Appl Artif Intell"},{"key":"3595_CR18","unstructured":"Alaparthi S, Mishra M (2020) Bidirectional encoder representations from transformers (bert): A sentiment analysis odyssey. arXiv preprint arXiv:2007.01127"},{"key":"3595_CR19","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown T, Mann B, Ryder N, Subbiah M, Kaplan JD, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A (2020) Language models are few-shot learners. Adv Neural Inf Process Syst 33:1877\u20131901","journal-title":"Adv Neural Inf Process Syst"},{"issue":"3","key":"3595_CR20","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab0e2e","volume":"16","author":"A Ameri","year":"2019","unstructured":"Ameri A, Akhaee MA, Scheme E, Englehart K (2019) Regression convolutional neural network for improved simultaneous emg control. J Neural Eng 16(3):036015","journal-title":"J Neural Eng"},{"key":"3595_CR21","doi-asserted-by":"publisher","first-page":"379","DOI":"10.3389\/fnins.2017.00379","volume":"11","author":"X Zhai","year":"2017","unstructured":"Zhai X, Jelfs B, Chan RH, Tin C (2017) Self-recalibrating surface emg pattern recognition for neuroprosthesis control based on convolutional neural network. Front Neurosci 11:379","journal-title":"Front Neurosci"},{"key":"3595_CR22","doi-asserted-by":"crossref","unstructured":"Bao T, Zaidi A, Xie S, Zhang Z (2019) Surface-emg based wrist kinematics estimation using convolutional neural network. In: 2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp 1\u20134","DOI":"10.1109\/BSN.2019.8771100"},{"key":"3595_CR23","doi-asserted-by":"crossref","unstructured":"Amma C, Krings T, B\u00f6er J, Schultz T (2015) Advancing muscle-computer interfaces with high-density electromyography. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems, pp 929\u2013938","DOI":"10.1145\/2702123.2702501"},{"issue":"6","key":"3595_CR24","doi-asserted-by":"publisher","first-page":"2841","DOI":"10.1109\/JBHI.2023.3262316","volume":"27","author":"X Jiang","year":"2023","unstructured":"Jiang X, Nazarpour K, Dai C (2023) Explainable and robust deep forests for emg-force modeling. IEEE J Biomed Health Inform 27(6):2841\u20132852","journal-title":"IEEE J Biomed Health Inform"},{"issue":"1","key":"3595_CR25","doi-asserted-by":"publisher","first-page":"7244","DOI":"10.1038\/s41598-019-43676-8","volume":"9","author":"AE Olsson","year":"2019","unstructured":"Olsson AE, Sager P, Andersson E, Bj\u00f6rkman A, Male\u0161evi\u0107 N, Antfolk C (2019) Extraction of multi-labelled movement information from the raw hd-semg image with time-domain depth. Sci Rep 9(1):7244","journal-title":"Sci Rep"},{"key":"3595_CR26","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"3595_CR27","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"issue":"1","key":"3595_CR28","first-page":"157","volume":"134","author":"Z Xu","year":"2023","unstructured":"Xu Z, Yu J, Xiang W, Zhu S, Hussain M, Liu B, Li J (2023) A novel se-cnn attention architecture for semg-based hand gesture recognition. CMES-Comput Model Eng Sci 134(1):157\u2013177","journal-title":"CMES-Comput Model Eng Sci"},{"issue":"7","key":"3595_CR29","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1109\/TBME.2003.813539","volume":"50","author":"K Englehart","year":"2003","unstructured":"Englehart K, Hudgins B (2003) A robust, real-time control scheme for multifunction myoelectric control. IEEE Trans Biomed Eng 50(7):848\u2013854","journal-title":"IEEE Trans Biomed Eng"},{"issue":"10","key":"3595_CR30","doi-asserted-by":"publisher","first-page":"1710","DOI":"10.3390\/sym12101710","volume":"12","author":"MG Asogbon","year":"2020","unstructured":"Asogbon MG, Samuel OW, Jiang Y, Wang L, Geng Y, Sangaiah AK, Chen S, Fang P, Li G (2020) Appropriate feature set and window parameters selection for efficient motion intent characterization towards intelligently smart emg-pr system. Symmetry 12(10):1710","journal-title":"Symmetry"},{"key":"3595_CR31","doi-asserted-by":"publisher","first-page":"2157","DOI":"10.1109\/TNSRE.2022.3194246","volume":"30","author":"X Jiang","year":"2022","unstructured":"Jiang X, Liu X, Fan J, Dai C, Clancy EA, Chen W (2022) Random channel masks for regularization of least squares-based finger emg-force modeling to improve cross-day performance. IEEE Trans Neural Syst Rehabil Eng 30:2157\u20132167","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"3595_CR32","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, VanderPlas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay \u00c9 (2011) Scikit-learn: machine learning in python. J Mach Learn Res 12:2825\u20132830","journal-title":"J Mach Learn Res"},{"key":"3595_CR33","unstructured":"Paszke A, Gross S, Massa F, Lerer A, Bradbury J, Chanan G, Killeen T, Lin Z, Gimelshein N, Antiga L, Desmaison A, Kopf A, Yang E, DeVito Z, Raison M, Tejani A, Chilamkurthy S, Steiner B, Fang L, Bai J, Chintala S (2019) PyTorch: An imperative style, high-performance deep learning library. Adv Neural Inf Proc Syst 32"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-026-03595-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-026-03595-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-026-03595-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T08:23:25Z","timestamp":1786523005000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-026-03595-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":33,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,7]]}},"alternative-id":["3595"],"URL":"https:\/\/doi.org\/10.1007\/s11517-026-03595-z","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"14 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare there are no conflicts of interest regarding the publication of this paper.","order":1,"name":"Ethics","label":"Conflicts of Interest","group":{"name":"EthicsHeading","label":"Declarations"}}]}}