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In this paper, we discuss a solution to this problem based on a novel step\u2010by\u2010step method of feature extraction and pattern classification for multiclass MI\u2010EEG signals. First, the training data from all subjects is merged and enlarged through autoencoder to meet the need for massive amounts of data while reducing the bad effect on signal recognition because of randomness, instability, and individual variability of EEG data. Second, an end\u2010to\u2010end sharing structure with attention\u2010based time\u2010incremental shallow convolution neural network is proposed. Shallow convolution neural network (SCNN) and bidirectional long short\u2010term memory (BiLSTM) network are used to extract frequency\u2010spatial domain features and time\u2010series features of EEG signals, respectively. Then, the attention model is introduced into the feature fusion layer to dynamically weight these extracted temporal\u2010frequency\u2010spatial domain features, which greatly contributes to the reduction of feature redundancy and the improvement of classification accuracy. At last, validation tests using BCI Competition IV 2a data sets show that classification accuracy and kappa coefficient have reached 82.7\u2009\u00b1\u20095.57% and 0.78\u2009\u00b1\u20090.074, which can strongly prove its advantages in improving classification accuracy and reducing individual difference among different subjects from the same network.<\/jats:p>","DOI":"10.1155\/2021\/6613105","type":"journal-article","created":{"date-parts":[[2021,2,18]],"date-time":"2021-02-18T21:50:20Z","timestamp":1613685020000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Novel Time\u2010Incremental End\u2010to\u2010End Shared Neural Network with Attention\u2010Based Feature Fusion for Multiclass Motor Imagery Recognition"],"prefix":"10.1155","volume":"2021","author":[{"given":"Shidong","family":"Lian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2456-3567","authenticated-orcid":false,"given":"Jialin","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guokun","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3185-0254","authenticated-orcid":false,"given":"Xia","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huilin","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,2,18]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/aaf12e"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2019.00822"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.array.2019.100003"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/9374802"},{"key":"e_1_2_9_5_2","first-page":"72","article-title":"An efficient hardware implementation for a motor imagery brain computer interface system","volume":"26","author":"Malekmohammadi A.","year":"2019","journal-title":"Scientia Iranica"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/1742862"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-018-1146-8"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2019.101592"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10936-018-9595-2"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2019.00573"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.21037\/qims.2020.02.01"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3531-0"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2019.107003"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2020.108833"},{"key":"e_1_2_9_15_2","doi-asserted-by":"crossref","unstructured":"LiM.-A. 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