Noninvasive EEG-Based Intelligent Mobile Robots: A Systematic Review

IF 6.4 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Automation Science and Engineering Pub Date : 2024-09-12 DOI:10.1109/TASE.2024.3441055
Hongqi Li;Xiaoya Li;José R. del Millán
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Abstract

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. Note to Practitioners—The brain-computer interfaces (BCIs) can provide a novel and feasible way to convey the users’ intentions to the terminal devices through the brain signals, which has exhibited emerging prospects in both civil and military applications thus having attracted increasing interests in researchers, industries, and government. The integration of noninvasive electroencephalogram (EEG)-based BCIs and expanded wheeled robotics have potentials to improve the human daily life with enhanced level of mobility, exhibiting significant socioeconomic impacts. This paper provides a systematic review of the EEG-based intelligent mobile robots from the aspects of key milestones, key techniques, and performance evaluation. To bring such the next generation assistive products from the laboratory to real applications, this paper further highlights the remaining challenges and shed light on the potential future work.
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基于无创脑电图的智能移动机器人:系统综述
大脑控制的移动机器人可以为严重身体残疾的人提供恢复行动能力的机会,并使健康人在特定环境中有更大的可达范围,这在过去二十年中得到了蓬勃发展。本文对无创脑电图智能移动机器人进行了系统的综述。首先介绍了系统的总体架构和基本概念、典型的系统类型以及系统整体设计的主要研究工作。然后,对脑机接口、控制策略、机器人智能等相关关键技术进行了综述,阐述了整个系统的研究进展。系统性能评估是关键和复杂的,本文总结了招募参与者的条件、实验方案、任务和环境,重点介绍了BMI性能、导航性能、系统鲁棒性和用户的评估指标。我们进一步强调了仍存在的挑战和未来工作的潜在研究方向。本研究提供了信息概要,旨在增强当前对基于脑电图的移动机器人设备的理解,并提出未来的观点。从业人员注意:脑机接口(bci)提供了一种新颖可行的方式,通过脑信号将用户的意图传递给终端设备,在民用和军事应用中都显示出新兴的前景,从而引起了研究人员、行业和政府的越来越多的兴趣。基于无创脑电图(EEG)的脑机接口(bci)与扩展轮式机器人的整合,有可能改善人类的日常生活,提高行动能力,并表现出显著的社会经济影响。本文从关键里程碑、关键技术、性能评价等方面对基于脑电图的智能移动机器人进行了系统综述。为了将这些新一代的辅助产品从实验室带到实际应用中,本文进一步强调了仍然存在的挑战,并阐明了未来可能的工作。
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来源期刊
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Automation Science and Engineering 工程技术-自动化与控制系统
CiteScore
12.50
自引率
14.30%
发文量
404
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Automation Science and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. T-ASE welcomes results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, security, service, supply chains, and transportation. T-ASE addresses a research community willing to integrate knowledge across disciplines and industries. For this purpose, each paper includes a Note to Practitioners that summarizes how its results can be applied or how they might be extended to apply in practice.
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