Georgios Prapas, Kosmas Glavas, A. Tzallas, Katerina D. Tzimourta, N. Giannakeas, M. Tsipouras
{"title":"Motor Imagery Approach for BCI Game Development","authors":"Georgios Prapas, Kosmas Glavas, A. Tzallas, Katerina D. Tzimourta, N. Giannakeas, M. Tsipouras","doi":"10.1109/SEEDA-CECNSM57760.2022.9932937","DOIUrl":null,"url":null,"abstract":"Brain-computer interface (BCI) is a rapidly growing field with various applications in many domains such as medical, gaming and lifestyle. This paper presents a 3D non-invasive BCI game. Muse 2 headband is used for acquiring electroencephalogram (EEG) data and OpenViBE platform for processing the raw signals and classification. The game is developed in Unity game Engine. Several subjects are included in the study and EEG signals are recorded for three different mental states i.e. left and right Motor Imagery and eye blink, before playing the game for ten times, aiming to collect coins. Average classification result is 94.86% and average coins collected from the users is 30.8 out of 50 coins. Furthermore, longer periods of playing the game leads to increased control over the game.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"83 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"计算机工程与设计","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Brain-computer interface (BCI) is a rapidly growing field with various applications in many domains such as medical, gaming and lifestyle. This paper presents a 3D non-invasive BCI game. Muse 2 headband is used for acquiring electroencephalogram (EEG) data and OpenViBE platform for processing the raw signals and classification. The game is developed in Unity game Engine. Several subjects are included in the study and EEG signals are recorded for three different mental states i.e. left and right Motor Imagery and eye blink, before playing the game for ten times, aiming to collect coins. Average classification result is 94.86% and average coins collected from the users is 30.8 out of 50 coins. Furthermore, longer periods of playing the game leads to increased control over the game.
期刊介绍：
Computer Engineering and Design is supervised by China Aerospace Science and Industry Corporation and sponsored by the 706th Institute of the Second Academy of China Aerospace Science and Industry Corporation. It was founded in 1980. The purpose of the journal is to disseminate new technologies and promote academic exchanges. Since its inception, it has adhered to the principle of combining depth and breadth, theory and application, and focused on reporting cutting-edge and hot computer technologies. The journal accepts academic papers with innovative and independent academic insights, including papers on fund projects, award-winning research papers, outstanding papers at academic conferences, doctoral and master's theses, etc.
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