{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T17:26:38Z","timestamp":1776101198009,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,11,6]],"date-time":"2022-11-06T00:00:00Z","timestamp":1667692800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Small and Medium-sized Enterprises (SMEs) and Startups (MSS), Korea,","award":["S3246057"],"award-info":[{"award-number":["S3246057"]}]},{"name":"Ministry of Small and Medium-sized Enterprises (SMEs) and Startups (MSS), Korea,","award":["P0016977"],"award-info":[{"award-number":["P0016977"]}]},{"DOI":"10.13039\/501100003661","name":"Korea Institute for Advancement of Technology","doi-asserted-by":"publisher","award":["S3246057"],"award-info":[{"award-number":["S3246057"]}],"id":[{"id":"10.13039\/501100003661","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003661","name":"Korea Institute for Advancement of Technology","doi-asserted-by":"publisher","award":["P0016977"],"award-info":[{"award-number":["P0016977"]}],"id":[{"id":"10.13039\/501100003661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Rapid advancements in the medical field have drawn much attention to automatic emotion classification from EEG data. People\u2019s emotional states are crucial factors in how they behave and interact physiologically. The diagnosis of patients\u2019 mental disorders is one potential medical use. When feeling well, people work and communicate more effectively. Negative emotions can be detrimental to both physical and mental health. Many earlier studies that investigated the use of the electroencephalogram (EEG) for emotion classification have focused on collecting data from the whole brain because of the rapidly developing science of machine learning. However, researchers cannot understand how various emotional states and EEG traits are related. This work seeks to classify EEG signals\u2019 positive, negative, and neutral emotional states by using a stacking-ensemble-based classification model that boosts accuracy to increase the efficacy of emotion classification using EEG. The selected features are used to train a model that was created using a random forest, light gradient boosting machine, and gradient-boosting-based stacking ensemble classifier (RLGB-SE), where the base classifiers random forest (RF), light gradient boosting machine (LightGBM), and gradient boosting classifier (GBC) were used at level 0. The meta classifier (RF) at level 1 is trained using the results from each base classifier to acquire the final predictions. The suggested ensemble model achieves a greater classification accuracy of 99.55%. Additionally, while comparing performance indices, the suggested technique outperforms as compared with the base classifiers. Comparing the proposed stacking strategy to state-of-the-art techniques, it can be seen that the performance for emotion categorization is promising.<\/jats:p>","DOI":"10.3390\/s22218550","type":"journal-article","created":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T03:02:22Z","timestamp":1667790142000},"page":"8550","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["EEG-Based Emotion Classification Using Stacking Ensemble Approach"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1648-6095","authenticated-orcid":false,"given":"Subhajit","family":"Chatterjee","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Jeju National University, Jeju 63243, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1107-9941","authenticated-orcid":false,"given":"Yung-Cheol","family":"Byun","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Major of Electronic Engineering, Institute of Information Science & Technology, Jeju National University, Jeju 63243, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1080\/02699930802204677","article-title":"Measures of emotion: A review","volume":"23","author":"Mauss","year":"2009","journal-title":"Cogn. 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