{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T01:32:46Z","timestamp":1778808766327,"version":"3.51.4"},"reference-count":66,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T00:00:00Z","timestamp":1652659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Institution Scientific Research Operating Foundation of Heilongjiang Province","award":["2018002"],"award-info":[{"award-number":["2018002"]}]},{"name":"Basic Institution Scientific Research Operating Foundation of Heilongjiang Province","award":["JM201911"],"award-info":[{"award-number":["JM201911"]}]},{"name":"HLJU Heilongjiang University","award":["2018002"],"award-info":[{"award-number":["2018002"]}]},{"name":"HLJU Heilongjiang University","award":["JM201911"],"award-info":[{"award-number":["JM201911"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>With the widespread use of emotion recognition, cross-subject emotion recognition based on EEG signals has become a hot topic in affective computing. Electroencephalography (EEG) can be used to detect the brain\u2019s electrical activity associated with different emotions. The aim of this research is to improve the accuracy by enhancing the generalization of features. A Multi-Classifier Fusion method based on mutual information with sequential forward floating selection (MI_SFFS) is proposed. The dataset used in this paper is DEAP, which is a multi-modal open dataset containing 32 EEG channels and multiple other physiological signals. First, high-dimensional features are extracted from 15 EEG channels of DEAP after using a 10 s time window for data slicing. Second, MI and SFFS are integrated as a novel feature-selection method. Then, support vector machine (SVM), k-nearest neighbor (KNN) and random forest (RF) are employed to classify positive and negative emotions to obtain the output probabilities of classifiers as weighted features for further classification. To evaluate the model performance, leave-one-out cross-validation is adopted. Finally, cross-subject classification accuracies of 0.7089, 0.7106 and 0.7361 are achieved by the SVM, KNN and RF classifiers, respectively. The results demonstrate the feasibility of the model by splicing different classifiers\u2019 output probabilities as a portion of the weighted features.<\/jats:p>","DOI":"10.3390\/e24050705","type":"journal-article","created":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T13:06:23Z","timestamp":1652706383000},"page":"705","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Multi-Classifier Fusion Based on MI\u2013SFFS for Cross-Subject Emotion Recognition"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9014-685X","authenticated-orcid":false,"given":"Haihui","family":"Yang","sequence":"first","affiliation":[{"name":"College of Electronic Engineering, Heilongjiang University, Harbin 150080, China"},{"name":"Key Laboratory of Information Fusion Estimation and Detection, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiguo","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Heilongjiang University, Harbin 150080, China"},{"name":"Key Laboratory of Information Fusion Estimation and Detection, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengwei","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Heilongjiang University, Harbin 150080, China"},{"name":"Key Laboratory of Information Fusion Estimation and Detection, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guobing","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Heilongjiang University, Harbin 150080, China"},{"name":"Key Laboratory of Information Fusion Estimation and Detection, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102551","DOI":"10.1016\/j.jretconser.2021.102551","article-title":"The future of service: The power of emotion in human-robot interaction","volume":"61","author":"Chuah","year":"2021","journal-title":"J. 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