{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T14:28:21Z","timestamp":1772202501351,"version":"3.50.1"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T00:00:00Z","timestamp":1677110400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T00:00:00Z","timestamp":1677110400000},"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":["61563032"],"award-info":[{"award-number":["61563032"]}],"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":["61963025"],"award-info":[{"award-number":["61963025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Fund Project of Industrial Process Advanced Control of Gansu Province","award":["2019KFJJ02"],"award-info":[{"award-number":["2019KFJJ02"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s11517-023-02793-3","type":"journal-article","created":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T01:02:51Z","timestamp":1677114171000},"page":"1581-1602","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Multi-band spatial feature extraction and classification for motor imaging EEG signals based on OSFBCSP-GAO-SVM model"],"prefix":"10.1007","volume":"61","author":[{"given":"Yong","family":"Shang","sequence":"first","affiliation":[]},{"given":"Xing","family":"Gao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3607-6536","authenticated-orcid":false,"given":"Aimin","family":"An","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,23]]},"reference":[{"key":"2793_CR1","unstructured":"Janapati R, Dalal V, Sengupta R (2021) Advances in modern EEG-BCI signal processing: a review. Materials Today: Proceedings"},{"issue":"5","key":"2793_CR2","first-page":"743","volume":"43","author":"W-Z Chen","year":"2017","unstructured":"Chen W-Z, Li M-Y (2017) Multiple feature extraction based on ensemble empirical mode decomposition for motor imagery EEG recognition tasks. Acta Autom Sin 43(5):743\u2013752","journal-title":"Acta Autom Sin"},{"key":"2793_CR3","doi-asserted-by":"publisher","first-page":"102741","DOI":"10.1016\/j.bspc.2021.102741","volume":"68","author":"W Mumtaz","year":"2021","unstructured":"Mumtaz W, Rasheed S, Irfan A (2021) Review of challenges associated with the EEG artifact removal methods. Biomed Sig Process Control 68:102741","journal-title":"Biomed Sig Process Control"},{"key":"2793_CR4","unstructured":"Walinjkar MA, Woods J Personalized wearable systems for real-time ECG classification and healthcare interoperability"},{"key":"2793_CR5","doi-asserted-by":"publisher","first-page":"1875","DOI":"10.1016\/j.procs.2021.08.193","volume":"192","author":"C Belkhiria","year":"2021","unstructured":"Belkhiria C, Peysakhovich V (2021) EOG metrics for cognitive workload detection. Procedia Comput Sci 192:1875\u20131884","journal-title":"Procedia Comput Sci"},{"key":"2793_CR6","doi-asserted-by":"publisher","first-page":"103576","DOI":"10.1016\/j.bspc.2022.103576","volume":"75","author":"Y Zou","year":"2022","unstructured":"Zou Y, Zhao X, Chu Y, Xu W, Han J, Li W (2022) A supervised independent component analysis algorithm for motion imagery-based brain computer interface. Biomed Sig Process Control 75:103576","journal-title":"Biomed Sig Process Control"},{"key":"2793_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-3261-0","volume-title":"Time series analysis and its applications, vol 3","author":"RH Shumway","year":"2000","unstructured":"Shumway RH, Stoffer DS, Stoffer DS (2000) Time series analysis and its applications, vol 3. Springer, Berlin"},{"issue":"7","key":"2793_CR8","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1109\/34.192463","volume":"11","author":"SG Mallat","year":"1989","unstructured":"Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674\u2013693","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2793_CR9","doi-asserted-by":"publisher","first-page":"104969","DOI":"10.1016\/j.compbiomed.2021.104969","volume":"139","author":"AB Buriro","year":"2021","unstructured":"Buriro AB, Ahmed B, Baloch G, Ahmed J, Shoorangiz R, Weddell SJ, Jones RD (2021) Classification of alcoholic EEG signals using wavelet scattering transform-based features. Comput Biol Med 139:104969","journal-title":"Comput Biol Med"},{"key":"2793_CR10","doi-asserted-by":"crossref","unstructured":"Prathama YdBH, Shapiai MI, Aris SAM, Ibrahim Z, Jaafar J, Fauzi H (2017) Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification. In: Asian simulation conference. Springer, pp 591\u2013604","DOI":"10.1007\/978-981-10-6463-0_51"},{"issue":"25","key":"2793_CR11","doi-asserted-by":"publisher","first-page":"17521","DOI":"10.1007\/s11042-020-08675-2","volume":"79","author":"A Hekmatmanesh","year":"2020","unstructured":"Hekmatmanesh A, Wu H, Jamaloo F, Li M, Handroos H (2020) A combination of CSP-based method with soft margin SVM classifier and generalized RBF kernel for imagery-based brain computer interface applications. Multimed. Tools Appl. 79(25):17521\u201317549","journal-title":"Multimed. Tools Appl."},{"key":"2793_CR12","doi-asserted-by":"crossref","unstructured":"Hekmatmanesh A, Nardelli P HJ, Handroos H (2021) Review of the state-of-the-art of brain-controlled vehicles. IEEE Access","DOI":"10.1109\/ACCESS.2021.3100700"},{"key":"2793_CR13","doi-asserted-by":"crossref","unstructured":"Ang KK, Chin ZY, Zhang H, Guan C (2011) Composite filter bank common spatial pattern for motor imagery-based brain-computer interface. In: 2011 IEEE symposium on computational intelligence, cognitive algorithms, mind, and brain (CCMB). IEEE, pp 1\u20135","DOI":"10.1109\/CCMB.2011.5952108"},{"key":"2793_CR14","doi-asserted-by":"publisher","first-page":"109496","DOI":"10.1016\/j.jneumeth.2022.109496","volume":"371","author":"M Li","year":"2022","unstructured":"Li M, Zhang P, Yang G, Xu G, Guo M, Liao W (2022) A fisher linear discriminant analysis classifier fused with na\u00efve Bayes for simultaneous detection in an asynchronous brain-computer interface. J Neurosci Methods 371:109496","journal-title":"J Neurosci Methods"},{"key":"2793_CR15","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.procs.2018.10.392","volume":"143","author":"A Bablani","year":"2018","unstructured":"Bablani A, Edla DR, Dodia S (2018) Classification of EEG data using k-nearest neighbor approach for concealed information test. Procedia Comput Sci 143:242\u2013249","journal-title":"Procedia Comput Sci"},{"key":"2793_CR16","doi-asserted-by":"publisher","first-page":"109425","DOI":"10.1016\/j.jneumeth.2021.109425","volume":"366","author":"T Thenmozhi","year":"2022","unstructured":"Thenmozhi T, Helen R (2022) Feature selection using extreme gradient boosting Bayesian optimization to upgrade the classification performance of motor imagery signals for BCI. J Neurosci Methods 366:109425","journal-title":"J Neurosci Methods"},{"key":"2793_CR17","doi-asserted-by":"publisher","first-page":"1523","DOI":"10.1016\/j.procs.2018.05.116","volume":"132","author":"DR Edla","year":"2018","unstructured":"Edla DR, Mangalorekar K, Dhavalikar G, Dodia S (2018) Classification of EEG data for human mental state analysis using random forest classifier. Procedia Comput Sci 132:1523\u20131532","journal-title":"Procedia Comput Sci"},{"key":"2793_CR18","doi-asserted-by":"crossref","unstructured":"Iversen JR, Makeig S (2019) MEG\/EEG data analysis using EEGLAB. Magnetoencephalography Sig Dyn Cortical Netw, 391\u2013406","DOI":"10.1007\/978-3-030-00087-5_8"},{"key":"2793_CR19","doi-asserted-by":"crossref","unstructured":"Islam MK, Rastegarnia A (2019) Probability mapping based artifact detection and wavelet denoising based artifact removal from scalp EEG for BCI applications. In: 2019 IEEE 4th international conference on computer and communication systems (ICCCS). IEEE, pp 243\u2013247","DOI":"10.1109\/CCOMS.2019.8821739"},{"issue":"1","key":"2793_CR20","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/s11760-020-01722-3","volume":"15","author":"S Lei","year":"2021","unstructured":"Lei S, Lu M, Lin J, Zhou X, Yang X (2021) Remote sensing image denoising based on improved semi-soft threshold. Sig Image Video Process 15(1):73\u201381","journal-title":"Sig Image Video Process"},{"key":"2793_CR21","doi-asserted-by":"publisher","first-page":"107224","DOI":"10.1016\/j.apacoust.2020.107224","volume":"163","author":"V Bajaj","year":"2020","unstructured":"Bajaj V, Taran S, Khare SK, Sengur A (2020) Feature extraction method for classification of alertness and drowsiness states EEG signals. Appl Acoust 163:107224","journal-title":"Appl Acoust"},{"key":"2793_CR22","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.patrec.2016.08.013","volume":"84","author":"M Ring","year":"2016","unstructured":"Ring M, Eskofier BM (2016) An approximation of the gaussian RBF kernel for efficient classification with SVMs. Pattern Recogn Lett 84:107\u2013113","journal-title":"Pattern Recogn Lett"},{"key":"2793_CR23","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.patrec.2017.04.013","volume":"94","author":"J Jebadurai","year":"2017","unstructured":"Jebadurai J, Peter JD (2017) SK-SVR: sigmoid kernel support vector regression based in-scale single image super-resolution. Pattern Recogn Lett 94:144\u2013153","journal-title":"Pattern Recogn Lett"},{"key":"2793_CR24","doi-asserted-by":"crossref","unstructured":"Hekmatmanesh A, Jamaloo F, Wu H, Handroos H, Kilpel\u00e4inen A (2018) Common spatial pattern combined with kernel linear discriminate and generalized radial basis function for motor imagery-based brain computer interface applications. In: AIP conference proceedings, vol 1956. AIP Publishing LLC, p 020003","DOI":"10.1063\/1.5034255"},{"key":"2793_CR25","doi-asserted-by":"crossref","unstructured":"Hekmatmanesh A, Noori SMR, Mikaili M (2014) Sleep spindle detection using modified extreme learning machine generalized radial basis function method. In: 2014 22nd Iranian conference on electrical engineering (ICEE). IEEE, pp 1898\u20131902","DOI":"10.1109\/IranianCEE.2014.6999850"},{"key":"2793_CR26","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1016\/j.procs.2019.02.085","volume":"150","author":"LA Demidova","year":"2019","unstructured":"Demidova LA, Egin MM, Tishkin RV (2019) A self-tuning multiobjective genetic algorithm with application in the SVM classification. Procedia Comput Sci 150:503\u2013510","journal-title":"Procedia Comput Sci"},{"issue":"4","key":"2793_CR27","doi-asserted-by":"publisher","first-page":"461","DOI":"10.24846\/v27i4y201810","volume":"27","author":"MA Panhwar","year":"2018","unstructured":"Panhwar MA, Deng Z, Khuhro SA, Hakro DN (2018) Distance based energy optimization through improved fitness function of genetic algorithm in wireless sensor network. Stud Inform Control 27 (4):461\u2013468","journal-title":"Stud Inform Control"},{"key":"2793_CR28","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.optlastec.2014.12.022","volume":"70","author":"SJ Patel","year":"2015","unstructured":"Patel SJ, Kheraj V (2015) Optimization of the genetic operators and algorithm parameters for the design of a multilayer anti-reflection coating using the genetic algorithm. Optics Laser Technol 70:94\u201399","journal-title":"Optics Laser Technol"},{"key":"2793_CR29","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1016\/j.eswa.2017.09.005","volume":"91","author":"MZ Islam","year":"2018","unstructured":"Islam MZ, Estivill-Castro V, Rahman MA, Bossomaier T (2018) Combining k-means and a genetic algorithm through a novel arrangement of genetic operators for high quality clustering. Expert Syst Appl 91:402\u2013417","journal-title":"Expert Syst Appl"},{"key":"2793_CR30","doi-asserted-by":"crossref","unstructured":"Malan NS, Sharma S (2021) Motor imagery EEG spectral-spatial feature optimization using dual-tree complex wavelet and neighbourhood component analysis. IRBM","DOI":"10.1016\/j.irbm.2021.01.002"},{"key":"2793_CR31","doi-asserted-by":"crossref","unstructured":"Das A K, Suresh Sundaram, Sundararajan Narasimhan (2016) A robust interval type-2 fuzzy inference based BCI system. In: 2016 IEEE international conference on systems, man, and cybernetics (SMC). IEEE, pp 004176\u2013004181","DOI":"10.1109\/SMC.2016.7844887"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-023-02793-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-023-02793-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-023-02793-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T04:25:37Z","timestamp":1683865537000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-023-02793-3"}},"subtitle":["EEG signal processing"],"short-title":[],"issued":{"date-parts":[[2023,2,23]]},"references-count":31,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["2793"],"URL":"https:\/\/doi.org\/10.1007\/s11517-023-02793-3","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,23]]},"assertion":[{"value":"29 June 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 February 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}