Emotional faces boost up steady-state visual responses for brain-computer interface

被引:36
|
作者
Bakardjian, Hovagim [1 ,2 ]
Tanaka, Toshihisa [1 ,2 ]
Cichocki, Andrzej [1 ]
机构
[1] RIKEN, Brain Sci Inst, Lab Adv Brain Signal Proc, Wako, Saitama 3510198, Japan
[2] Tokyo Univ Agr & Technol, Elect & Informat Engn Dept, Koganei, Tokyo, Japan
关键词
affective steady-state visual evoked potential; brain-computer interface; emotions; phase-locking value; steady-state visual evoked potentials; visual attention; POTENTIALS; ATTENTION;
D O I
10.1097/WNR.0b013e32834308b0
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Steady-state visual evoked potentials (SSVEPs) can be used successfully for brain-computer interfaces (BCI) with multiple commands and high information transfer rates. Inthis study, we investigated a novel affective SSVEP paradigm using flickering video clips of emotional human faces, and evaluated their performance in an 8-command BCI controlling a robotic arm in near real-time. Single-trial affective SSVEP responses, estimated using a new phase-locking value variability and a wavelet energy variability measures, were significantly enhanced compared with blurred-face flicker and standard checkerboards. For multicommand SSVEP-based BCI, affective face-flicker boosted up the information transfer rates from 50 to 64 bits/min, while reducing user fatigue and enhancing visual attention and reliability. In the 5-12 Hz flicker frequency range, the strongest affective SSVEP responses were obtained at 10 Hz. These findings suggest new directions for SSVEP-based neural applications, including affective BCI and enhanced steady-state clinical probes.© 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins.
引用
收藏
页码:121 / 125
页数:5
相关论文
共 50 条
  • [21] Steady-State Movement Related Potentials for Brain-Computer Interfacing
    Nazarpour, Kianoush
    Praamstra, Peter
    Miall, R. Chris
    Sanei, Saeid
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2009, 56 (08) : 2104 - 2113
  • [22] An auditory selective attention brain-computer interface system based on auditory steady-state response
    Wang, Yao
    Liu, Xin
    Cui, Hongyan
    Li, Zhaohui
    Chen, Xiaogang
    APPLIED ACOUSTICS, 2025, 228
  • [23] Dual-frequency steady-state visual evoked potential for brain computer interface
    Shyu, Kuo-Kai
    Lee, Po-Lei
    Liu, Yu-Ju
    Sie, Jyun-Jie
    NEUROSCIENCE LETTERS, 2010, 483 (01) : 28 - 31
  • [24] Steady-State Visual Evoked Potential-Based Brain-Computer Interface Using a Novel Visual Stimulus with Quick Response (QR) Code Pattern
    Siribunyaphat, Nannaphat
    Punsawad, Yunyong
    SENSORS, 2022, 22 (04)
  • [25] Enhancing the classification accuracy of Steady-State Visual Evoked Potential-based Brain-Computer Interface using Component Synchrony Measure
    Ng, Kian B.
    Cunnington, Ross
    Bradley, Andrew P.
    2012 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2012,
  • [26] Multisymbol Time Division Coding for High-Frequency Steady-State Visual Evoked Potential-Based Brain-Computer Interface
    Ye, Xiaochen
    Yang, Chen
    Chen, Yonghao
    Wang, Yijun
    Gao, Xiaorong
    Zhang, Hongxin
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2022, 30 : 1693 - 1704
  • [27] A Design of Brain-Computer Interface System for Steady-State Visual Evoked Potential Integrating Eye Movement Tracking and Target Dynamical Adjustment
    He L.
    Xie J.
    Yu H.
    Ren Z.
    Yang Y.
    Li M.
    Xu G.
    Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2021, 55 (10): : 87 - 95
  • [28] Development of a practical high frequency brain-computer interface based on steady-state visual evoked potentials using a single channel of EEG
    Ajami, Saba
    Mahnam, Amin
    Abootalebi, Vahid
    BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, 2018, 38 (01) : 106 - 114
  • [29] Brain-Computer Interface Based on Steady-State Visual Evoked Potential Using Quick-Response Code Pattern for Wheelchair Control
    Siribunyaphat, Nannaphat
    Punsawad, Yunyong
    SENSORS, 2023, 23 (04)
  • [30] Flexible boron-doped diamond spiral electrode for application in brain-computer interface based on steady-state visual evoked potential
    Yao, Yukun
    Sun, Yongyue
    Li, Hongji
    Xuan, Xiuwei
    Xu, Sheng
    Li, Mingji
    MEASUREMENT, 2023, 211