{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T12:04:54Z","timestamp":1785153894508,"version":"3.55.0"},"reference-count":32,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.bspc.2026.110880","type":"journal-article","created":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T07:33:25Z","timestamp":1782891205000},"page":"110880","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["Research on feature enhancement algorithms for electromyographic signals under vibration disturbance for gesture intent recognition"],"prefix":"10.1016","volume":"126","author":[{"given":"Yuxuan","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingchi","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7270-752X","authenticated-orcid":false,"given":"Jing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihong","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.bspc.2026.110880_b1","series-title":"Surface Electromyography: Physiology, Engineering, and Applications","first-page":"1","article-title":"Biophysics of the generation of EMG signals","author":"Merletti","year":"2016"},{"issue":"7","key":"10.1016\/j.bspc.2026.110880_b2","doi-asserted-by":"crossref","DOI":"10.3390\/bios12070516","article-title":"A review of EMG-, FMG-, and EIT-based biosensors and relevant human\u2013machine interactivities and biomedical applications","volume":"12","author":"Zheng","year":"2022","journal-title":"Biosensors"},{"issue":"1","key":"10.1016\/j.bspc.2026.110880_b3","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/MIM.2022.9693438","article-title":"Automated biomedical signal quality assessment of electromyograms: Current challenges and future prospects","volume":"25","author":"Raghu","year":"2022","journal-title":"IEEE Instrum. Meas. Mag."},{"key":"10.1016\/j.bspc.2026.110880_b4","first-page":"198","article-title":"The effect of hand-held vibrating tools on muscle activity and grip strength","author":"Widia","year":"2011","journal-title":"Aust. J. Basic Appl. Sci."},{"key":"10.1016\/j.bspc.2026.110880_b5","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s12239-020-0012-0","article-title":"Neck\/Shoulder muscle fatigue of military vehicle drivers exposed to whole-body vibration on field terrain road","volume":"21","author":"Park","year":"2020","journal-title":"Int. J Automot. Technol."},{"issue":"6","key":"10.1016\/j.bspc.2026.110880_b6","doi-asserted-by":"crossref","first-page":"1156","DOI":"10.1139\/H07-116","article-title":"The effects of whole-body vibration on upper- and lower-body EMG during static and dynamic contractions","volume":"32","author":"Hazell","year":"2007","journal-title":"Appl. Physiol. Nutr. Metab."},{"issue":"1","key":"10.1016\/j.bspc.2026.110880_b7","first-page":"169","article-title":"The effect of whole-body vibration frequency and amplitude on the myoelectric activity of vastus medialis and vastus lateralis","volume":"10","author":"Krol","year":"2011","journal-title":"J. Sport. Sci. Med."},{"issue":"9","key":"10.1016\/j.bspc.2026.110880_b8","doi-asserted-by":"crossref","first-page":"1166","DOI":"10.1016\/j.medengphy.2009.07.014","article-title":"Muscle motion and EMG activity in vibration treatment","volume":"31","author":"Fratini","year":"2009","journal-title":"Med. Eng. Phys."},{"key":"10.1016\/j.bspc.2026.110880_b9","doi-asserted-by":"crossref","first-page":"4880","DOI":"10.1038\/s41467-021-25152-y","article-title":"Ultra-conformal skin electrodes with synergistically enhanced conductivity for long-time and low-motion artifact epidermal electrophysiology","volume":"12","author":"Zhao","year":"2021","journal-title":"Nat. Commun."},{"issue":"12","key":"10.1016\/j.bspc.2026.110880_b10","doi-asserted-by":"crossref","first-page":"3371","DOI":"10.1109\/TBME.2019.2904398","article-title":"A modular, smart, and wearable system for high density sEMG detection","volume":"66","author":"Cerone","year":"2019","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"5","key":"10.1016\/j.bspc.2026.110880_b11","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1109\/TNSRE.2019.2910387","article-title":"Interference removal from electromyography based on independent component analysis","volume":"27","author":"Zheng","year":"2019","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"10.1016\/j.bspc.2026.110880_b12","series-title":"2025 International Conference on Digital Analysis and Processing, Intelligent Computation","first-page":"101","article-title":"Study on motion artifact denoise of surface electromyographic signals based on adaptive filtering method","author":"Xuechao","year":"2025"},{"key":"10.1016\/j.bspc.2026.110880_b13","series-title":"11th Mediterranean Conference on Medical and Biomedical Engineering and Computing 2007","article-title":"Acceleration driven adaptive filter to remove motion artifact from EMG recordings in whole body vibration","volume":"vol. 16","author":"Fratini","year":"2007"},{"key":"10.1016\/j.bspc.2026.110880_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106307","article-title":"Automated detection and removal of artifacts from sEMG signals based on fuzzy inference system and signal decomposition methods","volume":"94","author":"Ait Yous","year":"2024","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110880_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.jelekin.2023.102834","article-title":"Automatic selection of IMFs to denoise the sEMG signals using EMD","volume":"73","author":"Koppolu","year":"2023","journal-title":"J. Electromyography Kinesiol."},{"key":"10.1016\/j.bspc.2026.110880_b16","series-title":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society","first-page":"186","article-title":"Actor-critic reinforcement learning based algorithm for contaminant type identification in surface electromyography data","author":"Tosin","year":"2021"},{"key":"10.1016\/j.bspc.2026.110880_b17","series-title":"2024 Third International Conference on Power, Control and Computing Technologies, ICPC2T","first-page":"25","article-title":"Efficient contaminant identification in sEMG signals using machine learning","author":"Jena","year":"2024"},{"key":"10.1016\/j.bspc.2026.110880_b18","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117772","article-title":"Identification and removal of contaminants in sEMG recordings through a methodology based on fuzzy inference and actor-critic reinforcement learning","volume":"206","author":"Tosin","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.bspc.2026.110880_b19","doi-asserted-by":"crossref","first-page":"132882","DOI":"10.1109\/ACCESS.2020.3008901","article-title":"Feature extraction and classification of lower limb motion based on sEMG signals","volume":"8","author":"Shi","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.bspc.2026.110880_b20","series-title":"2013 IEEE 8th Conference on Industrial Electronics and Applications","first-page":"1492","article-title":"Surface electromyography (sEMG) feature extraction based on daubechies wavelets","author":"Elamvazuthi","year":"2013"},{"key":"10.1016\/j.bspc.2026.110880_b21","series-title":"TENCON 2017 - 2017 IEEE Region 10 Conference","first-page":"1624","article-title":"Classification of forearm movements from sEMG time domain features using machine learning algorithms","author":"Jose","year":"2017"},{"key":"10.1016\/j.bspc.2026.110880_b22","first-page":"3226","article-title":"Hb vsEMG signal classification with time domain and frequency domain features using LDA and ANN classifier","volume":"37","author":"Narayan","year":"2021","journal-title":"Mater. Today: Proc."},{"key":"10.1016\/j.bspc.2026.110880_b23","series-title":"2017 4th International Conference on Advanced Computing and Communication Systems","first-page":"1","article-title":"Time domain multi-feature extraction and classification of human hand movements using surface EMG","author":"Bhattacharya","year":"2017"},{"issue":"23","key":"10.1016\/j.bspc.2026.110880_b24","doi-asserted-by":"crossref","first-page":"16835","DOI":"10.1109\/JIOT.2021.3056126","article-title":"sEMG-based dynamic muscle fatigue classification using SVM with improved whale optimization algorithm","volume":"8","author":"Liu","year":"2021","journal-title":"IEEE Internet Things J."},{"issue":"2","key":"10.1016\/j.bspc.2026.110880_b25","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1109\/TBME.2020.3012783","article-title":"Real-time forecasting of sEMG features for trunk muscle fatigue using machine learning","volume":"68","author":"Moniri","year":"2021","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"8","key":"10.1016\/j.bspc.2026.110880_b26","doi-asserted-by":"crossref","DOI":"10.3390\/act14080378","article-title":"Continuous estimation of sEMG-based upper-limb joint angles in the time\u2013frequency domain using a scale temporal\u2013channel cross-encoder","volume":"14","author":"Han","year":"2025","journal-title":"Actuators"},{"key":"10.1016\/j.bspc.2026.110880_b27","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.cmpb.2017.10.024","article-title":"Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms","volume":"154","author":"Karthick","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.bspc.2026.110880_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118282","article-title":"sEMG time\u2013frequency features for hand movements classification","volume":"210","author":"Karheily","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.bspc.2026.110880_b29","series-title":"Mechanical vibration \u2014 Measurement and evaluation of human exposure to hand-transmitted vibration \u2014 Part 1: General requirements","author":"International Organization for Standardization","year":"2001"},{"key":"10.1016\/j.bspc.2026.110880_b30","series-title":"Directive 2002\/44\/EC on the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (vibration)","author":"The European Parliament and of the Council","year":"2002"},{"key":"10.1016\/j.bspc.2026.110880_b31","unstructured":"Ottobock, 8K50 mayo high cost-effectiveness myoelectric hand, https:\/\/www.ottobock.com.cn\/zh-cn\/pro-solutions\/upper-limb\/8k50. (Accessed 28 May 2026)."},{"issue":"6","key":"10.1016\/j.bspc.2026.110880_b32","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1016\/j.jelekin.2015.10.005","article-title":"Comparison of sEMG processing methods during whole-body vibration exercise","volume":"25","author":"Lienhard","year":"2015","journal-title":"J. Electromyography Kinesiol."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426014345?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426014345?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T11:34:40Z","timestamp":1785152080000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426014345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":32,"alternative-id":["S1746809426014345"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110880","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Research on feature enhancement algorithms for electromyographic signals under vibration disturbance for gesture intent recognition","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110880","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110880"}}