{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:36:07Z","timestamp":1771468567023,"version":"3.50.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T00:00:00Z","timestamp":1711065600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T00:00:00Z","timestamp":1711065600000},"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":["No. 61971169"],"award-info":[{"award-number":["No. 61971169"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Zhejiang Provincial Key Research and Development Program of China","award":["No.2021C03031"],"award-info":[{"award-number":["No.2021C03031"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["NO. LQ21H180005"],"award-info":[{"award-number":["NO. LQ21H180005"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s11517-024-03069-0","type":"journal-article","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T01:02:05Z","timestamp":1711069325000},"page":"2305-2318","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimizing motion imagery classification with limited channels using the common spatial pattern-based integrated algorithm"],"prefix":"10.1007","volume":"62","author":[{"given":"Shishi","family":"Chen","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9213-6313","authenticated-orcid":false,"given":"Xugang","family":"Xi","sequence":"additional","affiliation":[]},{"given":"Ting","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Hangcheng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Maofeng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Lihua","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhong","family":"L\u00fc","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,22]]},"reference":[{"key":"3069_CR1","doi-asserted-by":"publisher","unstructured":"Grosse-Wentrup M, Liefhold C, Gramann K, et al. (2009) Beamforming in noninvasive brain-computer interfaces [J]. IEEE Trans Bio-Med Eng.\u00a0https:\/\/doi.org\/10.1109\/TBME.2008.2009768","DOI":"10.1109\/TBME.2008.2009768"},{"key":"3069_CR2","doi-asserted-by":"crossref","unstructured":"Guan S, Wang J, Wang F (2020) Research on recognition of shoulder joint movement imagination based on BCI technology [C]. Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture, 163\u2013167","DOI":"10.1145\/3421766.3421805"},{"key":"3069_CR3","doi-asserted-by":"publisher","unstructured":"Elstob D, Secco E L (2016) A low cost EEG based BCI prosthetic using motor imagery [Z]. https:\/\/doi.org\/10.5121\/ijitcs.2016.6103","DOI":"10.5121\/ijitcs.2016.6103"},{"issue":"9","key":"3069_CR4","doi-asserted-by":"publisher","first-page":"1108","DOI":"10.3109\/02699052.2010.494591","volume":"24","author":"A Santamato","year":"2010","unstructured":"Santamato A, Panza F, Filoni S et al (2010) Effect of botulinum toxin type A, motor imagery and motor observation on motor function of hemiparetic upper limb after stroke [J]. Brain Inj 24(9):1108","journal-title":"Brain Inj"},{"key":"3069_CR5","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.brainres.2011.06.038","volume":"1407","author":"H Zhang","year":"2011","unstructured":"Zhang H, Xu L, Wang S et al (2011) Behavioral improvements and brain functional alterations by motor imagery training [J]. Brain Res 1407:38\u201346","journal-title":"Brain Res"},{"key":"3069_CR6","doi-asserted-by":"publisher","unstructured":"Pfurtscheller G, Brunner C, SCHL?GL A, et al. (2006) Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks [J]. Neuroimage, 31(1): 153\u20139. https:\/\/doi.org\/10.1016\/j.neuroimage.2005.12.003","DOI":"10.1016\/j.neuroimage.2005.12.003"},{"issue":"02","key":"3069_CR7","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1142\/S0129065715500021","volume":"25","author":"H Wang","year":"2015","unstructured":"Wang H, Zhang C, Shi T et al (2015) Real-time EEG-based detection of fatigue driving danger for accident prediction [J]. Int J Neural Syst 25(02):498\u2013369","journal-title":"Int J Neural Syst"},{"key":"3069_CR8","doi-asserted-by":"publisher","unstructured":"Kumar S, Sharma A, Tsunoda T (2019) Subject-specific-frequency-band for motor imagery EEG signal recognition based on common spatial spectral pattern, F[C]. https:\/\/doi.org\/10.1007\/978-3-030-29911-8_55","DOI":"10.1007\/978-3-030-29911-8_55"},{"issue":"2","key":"3069_CR9","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1109\/JBHI.2018.2832538","volume":"23","author":"Y Jiao","year":"2018","unstructured":"Jiao Y, Zhang Y, Chen X et al (2018) Sparse group representation model for motor imagery EEG classification [J]. IEEE J Biomed Health Inform 23(2):631\u2013641","journal-title":"IEEE J Biomed Health Inform"},{"issue":"2","key":"3069_CR10","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1109\/TBME.2014.2358536","volume":"62","author":"N Tomida","year":"2014","unstructured":"Tomida N, Tanaka T, Ono S et al (2014) Active data selection for motor imagery EEG classification [J]. IEEE Trans Biomed Eng 62(2):458\u2013467","journal-title":"IEEE Trans Biomed Eng"},{"key":"3069_CR11","unstructured":"Correa M, Leber E L (2011) Noise removal from EEG signals in polisomnographic records applying adaptive filters in cascade [M]. Adapt Filt Appl"},{"issue":"PP","key":"3069_CR12","first-page":"1","volume":"1","author":"J Jin","year":"2020","unstructured":"Jin J, Xiao R, Daly I et al (2020) Internal feature selection method of CSP based on L1-Norm and Dempster-Shafer theory [J]. IEEE Trans Neural Netw Learn Syst 1(PP):1\u201312","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"3069_CR13","doi-asserted-by":"publisher","unstructured":"Miao Y, Jin J, Daly I, et al. (2021) Learning common time-frequency-spatial patterns for motor imagery classification [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, PP(99): 1-. https:\/\/doi.org\/10.1109\/TNSRE.2021.3071140","DOI":"10.1109\/TNSRE.2021.3071140"},{"issue":"1","key":"3069_CR14","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab53f1","volume":"17","author":"U Talukdar","year":"2020","unstructured":"Talukdar U, Hazarika SM, Gan JQ (2020) Adaptive feature extraction in EEG-based motor imagery BCI: tracking mental fatigue [J]. J Neural Eng 17(1):016020","journal-title":"J Neural Eng"},{"key":"3069_CR15","doi-asserted-by":"publisher","unstructured":"Zhang Y, Zhou G, Jin J, et al. (2015) Optimizing spatial patterns with sparse filter bands for motor-imagery based brain\u2013computer interface [J]. J Neurosci Methods, 85\u201391. https:\/\/doi.org\/10.1016\/j.jneumeth.2015.08.004","DOI":"10.1016\/j.jneumeth.2015.08.004"},{"key":"3069_CR16","doi-asserted-by":"crossref","unstructured":"Jin Y, Mousavi M, Sa V (2018) Adaptive CSP with subspace alignment for subject-to-subject transfer in motor imagery brain-computer interfaces; proceedings of the 2018 6th International Conference on Brain and Computer Interface (BCI), F, [C]","DOI":"10.1109\/IWW-BCI.2018.8311494"},{"issue":"9","key":"3069_CR17","doi-asserted-by":"publisher","first-page":"3322","DOI":"10.1109\/TCYB.2018.2841847","volume":"49","author":"Y Zhang","year":"2018","unstructured":"Zhang Y, Nam CS, Zhou G et al (2018) (2018) Temporally constrained sparse group spatial patterns for motor imagery BCI [J]. IEEE transactions on cybernetics 49(9):3322\u201332","journal-title":"IEEE transactions on cybernetics"},{"issue":"3","key":"3069_CR18","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.irbm.2019.11.002","volume":"41","author":"SZ Zahid","year":"2020","unstructured":"Zahid SZ, Aqil M, Tufail M et al (2020) Online classification of multiple motor imagery tasks using filter bank based maximum-a-posteriori common spatial pattern filters [J]. IRBM 41(3):141\u2013150","journal-title":"IRBM"},{"key":"3069_CR19","doi-asserted-by":"publisher","first-page":"012044","DOI":"10.1088\/1742-6596\/1169\/1\/012044","volume":"1169","author":"J Guan","year":"2019","unstructured":"Guan J, Duan F (2019) The improvement of motor imagery based on spectral feature and transformation on multivariate empirical mode decomposition [J]. J Phys Conf Ser 1169:012044","journal-title":"J Phys Conf Ser"},{"key":"3069_CR20","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1007\/s10462-019-09694-8","volume":"53","author":"MZ Baig","year":"2020","unstructured":"Baig MZ, Aslam N, Shum HP (2020) Filtering techniques for channel selection in motor imagery EEG applications: a survey [J]. Artif Intell Rev 53:1207\u20131232","journal-title":"Artif Intell Rev"},{"key":"3069_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102574","volume":"68","author":"P Gaur","year":"2021","unstructured":"Gaur P, McCreadie K, Pachori RB et al (2021) An automatic subject specific channel selection method for enhancing motor imagery classification in EEG-BCI using correlation [J]. Biomed Signal Process Control 68:102574","journal-title":"Biomed Signal Process Control"},{"key":"3069_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2022.148075","volume":"1796","author":"T-C Wang","year":"2022","unstructured":"Wang T-C, Huang Y-Y, Duann J-R (2022) Sources of independent mu components reveal different brain areas involved in motor imagery, motor execution, and movement observation [J]. Brain Res 1796:148075","journal-title":"Brain Res"},{"issue":"1","key":"3069_CR23","doi-asserted-by":"publisher","first-page":"57","DOI":"10.3390\/brainsci12010057","volume":"12","author":"F Ferracuti","year":"2021","unstructured":"Ferracuti F, Iarlori S, Mansour Z et al (2021) Comparing between different sets of preprocessing, classifiers, and channels selection techniques to optimise motor imagery pattern classification system from EEG pattern recognition [J]. Brain Sci 12(1):57","journal-title":"Brain Sci"},{"key":"3069_CR24","doi-asserted-by":"crossref","unstructured":"Saha S K, Ali M S (2016) Data adaptive filtering approach to improve the classification accuracy of motor imagery for BCI; proceedings of the International Conference on Electrical & Computer Engineering, F, [C]","DOI":"10.1109\/ICECE.2016.7853902"},{"issue":"9","key":"3069_CR25","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1103\/PhysRevLett.45.712","volume":"45","author":"NH Packard","year":"1980","unstructured":"Packard NH, Crutchfield JP, Farmer JD et al (1980) (1980) Geometry from a time series [J]. Physical review letters 45(9):712","journal-title":"Physical review letters"},{"key":"#cr-split#-3069_CR26.1","unstructured":"Takens F (2006) Detecting strange attractors in turbulence"},{"key":"#cr-split#-3069_CR26.2","unstructured":"proceedings of the Dynamical Systems and Turbulence, Warwick 1980: proceedings of a symposium held at the University of Warwick 1979\/80, F, [C]. Springer"},{"key":"3069_CR27","doi-asserted-by":"publisher","first-page":"1240323","DOI":"10.1155\/2017\/1240323","volume":"2017","author":"TN Alotaiby","year":"2017","unstructured":"Alotaiby TN, Alshebeili SA, Alotaibi FM et al (2017) Epileptic seizure prediction using CSP and LDA for scalp EEG signals [J]. Computational Intelligence and Neuroscience 2017:1240323. https:\/\/doi.org\/10.1155\/2017\/1240323","journal-title":"Computational Intelligence and Neuroscience"},{"key":"3069_CR28","doi-asserted-by":"crossref","unstructured":"Wang Y, Shen X, Peng Z (2018) Research of EEG recognition algorithm based on motor imagery, F, [C]","DOI":"10.1109\/ICRAS.2018.8442383"},{"key":"3069_CR29","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1109\/TNSRE.2021.3055276","volume":"29","author":"C Li","year":"2021","unstructured":"Li C, Zhou W, Liu G et al (2021) Seizure onset detection using empirical mode decomposition and common spatial pattern [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering 29:458\u201367","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"key":"3069_CR30","first-page":"1","volume":"16","author":"C Brunner","year":"2008","unstructured":"Brunner C, Leeb R, M\u00fcller-Putz G et al (2008) BCI competition 2008\u2013Graz data set A [J]. Institute for Knowledge Discovery (Laboratory of Brain-Computer Interfaces). Graz Univ Technol 16:1\u20136","journal-title":"Graz Univ Technol"},{"issue":"1","key":"3069_CR31","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/14\/1\/016003","volume":"14","author":"YR Tabar","year":"2016","unstructured":"Tabar YR, Halici U (2016) A novel deep learning approach for classification of EEG motor imagery signals [J]. J Neural Eng 14(1):016003","journal-title":"J Neural Eng"},{"key":"3069_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.103190","volume":"71","author":"Y Han","year":"2022","unstructured":"Han Y, Wang B, Luo J et al (2022) A classification method for EEG motor imagery signals based on parallel convolutional neural network [J]. Biomed Signal Process Control 71:103190","journal-title":"Biomed Signal Process Control"},{"key":"3069_CR33","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3389\/fnins.2012.00039","volume":"6","author":"KK Ang","year":"2012","unstructured":"Ang KK, Chin ZY, Wang C et al (2012) Filter bank common spatial pattern algorithm on BCI competition IV datasets 2a and 2b [J]. Front Neurosci 6:39","journal-title":"Front Neurosci"},{"issue":"4","key":"3069_CR34","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1109\/THMS.2022.3168425","volume":"52","author":"Z Wang","year":"2022","unstructured":"Wang Z, He B, Zhou Y et al (2022) Incorporating EEG and EMG patterns to evaluate BCI-based long-term motor training [J]. IEEE Trans Human-Mach Syst 52(4):648\u2013657","journal-title":"IEEE Trans Human-Mach Syst"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-024-03069-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-024-03069-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-024-03069-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T11:14:18Z","timestamp":1722338058000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-024-03069-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,22]]},"references-count":35,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["3069"],"URL":"https:\/\/doi.org\/10.1007\/s11517-024-03069-0","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,22]]},"assertion":[{"value":"28 September 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 March 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All the experimental procedures were approved by the ethics committee of Dongyang People\u2019s Hospital of Zhejiang Province.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}