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However, long calibration time and lack of enough MI commands limit its use in practice. In order to enlarge the command set, we add the combinations of traditional MI commands as new commands into the command set. We also design an algorithm based on transfer learning so as to decrease the calibration time for collecting EEG signal and training model. We create feature extractor based on data from traditional commands and transfer patterns through the data from new commands. Through the comparison of the average accuracy between our algorithm and traditional algorithms and the visualization of spatial patterns in our algorithm, we find that the accuracy of our algorithm is much higher than traditional algorithms, especially as for the low-quality datasets. Besides, the visualization of spatial patterns is meaningful. The algorithm based on transfer learning takes the advantage of the information from source data. We enlarge the command set while shortening the calibration time, which is of significant importance to the MI-BCI application.<\/jats:p>","DOI":"10.1155\/2020\/6056383","type":"journal-article","created":{"date-parts":[[2020,12,15]],"date-time":"2020-12-15T19:50:06Z","timestamp":1608061806000},"page":"1-11","source":"Crossref","is-referenced-by-count":11,"title":["Task Transfer Learning for EEG Classification in Motor Imagery-Based BCI System"],"prefix":"10.1155","volume":"2020","author":[{"given":"Xuanci","family":"Zheng","sequence":"first","affiliation":[{"name":"College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9299-3251","authenticated-orcid":true,"given":"Jie","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2759-7084","authenticated-orcid":true,"given":"Hongfei","family":"Ji","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China"}]},{"given":"Lili","family":"Duan","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China"}]},{"given":"Maozhen","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electronic and Computer Engineering, Brunel University London, Uxbridge UB8 3PH, UK"}]},{"given":"Zilong","family":"Pang","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China"}]},{"given":"Jie","family":"Zhuang","sequence":"additional","affiliation":[{"name":"School of Psychology, Shanghai University of Sport, Shanghai 200438, China"}]},{"given":"Lu","family":"Rongrong","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation, Huashan Hospital, Fudan University, Shanghai 200040, China"}]},{"given":"Gao","family":"Tianhao","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation, Huashan Hospital, Fudan University, Shanghai 200040, China"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/aaf3f6"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1002\/ana.24390"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/iembs.2010.5626782"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2016.09.007"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2018.2830647"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2018.00696"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/S1388-2457(02)00057-3"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.116.016304"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2012.12.039"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1016\/S1388-2457(99)00141-8"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/86.808944"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/0013-4694(77)90092-X"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2019.2956488"},{"first-page":"17","article-title":"Multitask learning for brain-computer interfaces","author":"M. 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