Speech Imagery BCI Training Using Game with a Purpose

被引:0
|
作者
Selim, Abdulrahman Mohamed [1 ]
Rekrut, Maurice [1 ]
Barz, Michael [1 ,2 ]
Sonntag, Daniel [1 ,2 ]
机构
[1] German Res Ctr Artificial Intelligence DFKI, Saarbrucken, Germany
[2] Carl von Ossietzky Univ Oldenburg, Oldenburg, Germany
关键词
BCI; EEG; Imagined speech; Game with a purpose (GWAP); User study;
D O I
10.1145/3656650.3656654
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Games are used in multiple fields of brain-computer interface (BCI) research and applications to improve participants' engagement and enjoyment during electroencephalogram (EEG) data collection. However, despite potential benefits, no current studies have reported on implemented games for Speech Imagery BCI. Imagined speech is speech produced without audible sounds or active movement of the articulatory muscles. Collecting imagined speech EEG data is a time-consuming, mentally exhausting, and cumbersome process, which requires participants to read words off a computer screen and produce them as imagined speech. To improve this process for study participants, we implemented a maze-like game where a participant navigated a virtual robot capable of performing five actions that represented our words of interest while we recorded their EEG data. The study setup was evaluated with 15 participants. Based on their feedback, the game improved their engagement and enjoyment while resulting in a 69.10% average classification accuracy using a random forest classifier.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] The Impact of Different Visual Feedbacks in User Training on Motor Imagery Control in BCI
    Dariusz Zapała
    Piotr Francuz
    Ewelina Zapała
    Natalia Kopiś
    Piotr Wierzgała
    Paweł Augustynowicz
    Andrzej Majkowski
    Marcin Kołodziej
    Applied Psychophysiology and Biofeedback, 2018, 43 : 23 - 35
  • [32] The Impact of Different Visual Feedbacks in User Training on Motor Imagery Control in BCI
    Zapala, Dariusz
    Francuz, Piotr
    Zapala, Ewelina
    Kopis, Natalia
    Wierzgala, Piotr
    Augustynowicz, Pawel
    Majkowski, Andrzej
    Kolodziej, Marcin
    APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK, 2018, 43 (01) : 23 - 35
  • [33] Addressing Motor Imagery Performance Bias in Neurofeedback Training to Improve BCI Performance
    Connelly A.
    Li P.
    Rangpong P.
    Wilaiprasitporn T.
    Yagi T.
    IEEJ Transactions on Electronics, Information and Systems, 2024, 144 (05) : 431 - 437
  • [34] The LightGBM-based classification algorithm for Chinese characters speech imagery BCI system
    Pan, Hongguang
    Li, Zhuoyi
    Tian, Chen
    Wang, Li
    Fu, Yunpeng
    Qin, Xuebin
    Liu, Fei
    COGNITIVE NEURODYNAMICS, 2023, 17 (02) : 373 - 384
  • [35] Enhancement of cortical activation for motor imagery during BCI-FES training
    Wang, Zhongpeng
    Chen, Long
    Yi, Weibo
    Gu, Bin
    Liu, Shuang
    An, Xingwei
    Xu, Minpeng
    Qi, Hongzhi
    He, Feng
    Wan, Baikun
    Ming, Dong
    2018 40TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2018, : 2527 - 2530
  • [36] Speech Imagery Classification using Length-Wise Training based on Deep Learning
    Lee, Byeong-Hoo
    Kwon, Byeong-Hee
    Lee, Do-Yeun
    Jeong, Ji-Hoon
    2021 9TH IEEE INTERNATIONAL WINTER CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI), 2021, : 154 - 158
  • [37] Interactive Highway Construction Simulation Using Game Engine and Virtual Reality for Education and Training Purpose
    Mastli, Majid
    Zhang, Jiansong
    COMPUTING IN CIVIL ENGINEERING 2017: SENSING, SIMULATION, AND VISUALIZATION, 2017, : 399 - 406
  • [38] Using General-Purpose Graphic Processing Units for BCI Systems
    Wilson, J. Adam
    2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2011, : 4625 - 4628
  • [39] Game-based BCI training: Interactive design for individuals with cerebral palsy
    Scherer, Reinhold
    Schwarz, Andreas
    Mueller-Putz, Gernot R.
    Pammer-Schindler, Viktoria
    Lloria Garcia, Mariano
    2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS, 2015, : 3175 - 3180
  • [40] Neurofeedback-based motor imagery training for brain-computer interface (BCI)
    Hwang, Han-Jeong
    Kwon, Kiwoon
    Im, Chang-Hwang
    JOURNAL OF NEUROSCIENCE METHODS, 2009, 179 (01) : 150 - 156