Noninvasive EEG-Based Intelligent Mobile Robots: A Systematic Review

被引:1
|
作者
Li, Hongqi [1 ,2 ,3 ]
Li, Xiaoya [4 ]
Millan, Jose del R. [5 ,6 ]
机构
[1] Northwestern Polytech Univ, Sch Software, Xian 710072, Peoples R China
[2] Northwestern Polytech Univ Shenzhen, Res & Dev Inst, Shenzhen 518063, Peoples R China
[3] NPU, Yangtze River Delta Res Inst, Taicang 215400, Peoples R China
[4] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai 200240, Peoples R China
[5] Univ Texas Austin, Dept Elect & Comp Engn, Austin, TX 78712 USA
[6] Univ Texas Austin, Dept Neurol, Austin, TX 78712 USA
关键词
Robots; Mobile robots; Robot sensing systems; Electroencephalography; Wheelchairs; Brain-computer interfaces; Performance evaluation; intelligent robots; brain-controlled robotic systems; human-machine interaction; collaborative control; performance evaluation; BRAIN-COMPUTER-INTERFACE; WHEELCHAIR CONTROL; MOTOR IMAGERY; NEUROPHYSIOLOGICAL PROTOCOL; DROWSINESS ESTIMATION; ACTUATED WHEELCHAIR; MACHINE INTERFACES; EVOKED POTENTIALS; DRY ELECTRODE; REAL-TIME;
D O I
10.1109/TASE.2024.3441055
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Brain-controlled mobile robotics can provide restoration of mobility for individuals with severe physical disabilities and empower healthy people with a broader reachable range in particular environments, which have been flourished over the past twenty years. This paper conducts a systematic state-of-the-art overview of noninvasive EEG-based intelligent mobile robots. We first present the general architecture and basic concepts, typical system types, and main research efforts on the whole-system design. Then, relevant key techniques associated with the brain-machine interfaces (BMIs), control strategies, and robot intelligence are reviewed to elucidate the research progress of the overall system. System performance evaluation is critical and complicated, here we summarize the conditions of the recruited participants, the experimental protocol, tasks and environments, with an emphasis on evaluation metrics regarding BMI performance, navigation performance, system robustness, and the user. We further highlight the remaining challenges and the potential research directions of future work. This study with informative outline is envisioned to enhance current understanding and suggest the future perspectives on EEG-based mobile robotic devices .
引用
收藏
页码:6291 / 6315
页数:25
相关论文
共 50 条
  • [1] EEG-Based Brain-Controlled Mobile Robots: A Survey
    Bi, Luzheng
    Fan, Xin-An
    Liu, Yili
    IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 2013, 43 (02) : 161 - 176
  • [2] Electroencephalography (EEG) Based Control in Assistive Mobile Robots: A Review
    Krishnan, N. Murali
    Mariappan, Muralindran
    Muthukaruppan, Karthigayan
    Hijazi, Mohd Hanafi Ahmad
    Kitt, Wong Wei
    10TH CURTIN UNIVERSITY TECHNOLOGY SCIENCE AND ENGINEERING INTERNATIONAL CONFERENCE (CUTSE2015), 2016, 121
  • [3] A comprehensive review of EEG-based brain-computer interface paradigms
    Abiri, Reza
    Borhani, Soheil
    Sellers, Eric W.
    Jiang, Yang
    Zhao, Xiaopeng
    JOURNAL OF NEURAL ENGINEERING, 2019, 16 (01)
  • [4] Sleep assessment using EEG-based wearables - A systematic review
    de Gans, C. J.
    Burger, P.
    van den Ende, E. S.
    Hermanides, J.
    Nanayakkara, P. W. B.
    Gemke, R. J. B. J.
    Rutters, F.
    Stenvers, D. J.
    SLEEP MEDICINE REVIEWS, 2024, 76
  • [5] EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots
    Tariq, Madiha
    Trivailo, Pavel M.
    Simic, Milan
    FRONTIERS IN HUMAN NEUROSCIENCE, 2018, 12
  • [6] EEG-Based Neurohaptics Research: A Literature Review
    Alsuradi, Haneen
    Park, Wanjoo
    Eid, Mohamad
    IEEE ACCESS, 2020, 8 : 49313 - 49328
  • [7] Deep Learning in EEG-Based BCIs: A Comprehensive Review of Transformer Models, Advantages, Challenges, and Applications
    Abibullaev, Berdakh
    Keutayeva, Aigerim
    Zollanvari, Amin
    IEEE ACCESS, 2023, 11 : 127271 - 127301
  • [8] Mind Meets Robots: A Review of EEG-Based Brain-Robot Interaction Systems
    Zhang, Yuchong
    Rajabi, Nona
    Taleb, Farzaneh
    Matviienko, Andrii
    Ma, Yong
    Bjorkman, Marten
    Kragic, Danica Jensfelt
    INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2025,
  • [9] Motor-Imagery EEG-Based BCIs in Wheelchair Movement and Control: A Systematic Literature Review
    Palumbo, Arrigo
    Gramigna, Vera
    Calabrese, Barbara
    Ielpo, Nicola
    SENSORS, 2021, 21 (18)
  • [10] Exploration of EEG-Based Depression Biomarkers Identification Techniques and Their Applications: A Systematic Review
    Dev, Antora
    Roy, Nipa
    Islam, Md Kafiul
    Biswas, Chiranjeeb
    Ahmed, Helal Uddin
    Amin, Md Ashraful
    Sarker, Farhana
    Vaidyanathan, Ravi
    Mamun, Khondaker A.
    IEEE ACCESS, 2022, 10 : 16756 - 16781