Proceedings ArticleDOI
Hybrid brain/muscle-actuated control of an intelligent wheelchair
Zhijun Li,Shuangshuang Lei,Chun-Yi Su,Guanglin Li +3 more
- pp 19-25
TLDR
This paper presents a real-time hybrid brain/muscle interface to control a wheelchair directly to keep the disables recovering several motion capabilities by using noninvasive motor imagery Electroencephalography (EEG) and Electromyography (EMG).Abstract:
Brain-computer interface (BCI) controlled wheelchair robots can serve as powerful aids for severely disabled people in their daily life, especially to help them move voluntarily. In order to better understand human “thought”, owing to the development of the hybrid brain/muscle interface technique, in this paper, we present a real-time hybrid brain/muscle interface to control a wheelchair directly to keep the disables recovering several motion capabilities by using noninvasive motor imagery Electroencephalography (EEG) and Electromyography (EMG). The EMG and EEG signals from the users are extracted to control the motion of an intelligent wheelchair. Both signals processing consists of off-line training, online control evaluation, and real-time control. An algorithm called the common spatial patterns (CSP) is used in this human-robot system to extract the most discriminative spatial patterns pairs as features. The extensive experiments were conducted on the developed human-wheelchair systems to verify the proposed approaches.read more
Citations
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Journal ArticleDOI
Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review
Mamunur Rashid,Norizam Sulaiman,Anwar P. P. Abdul Majeed,Rabiu Muazu Musa,Ahmad Fakhri Ab. Nasir,Bifta Sama Bari,Sabira Khatun +6 more
TL;DR: This article provides a comprehensive review of the state-of-the-art of a complete BCI system and a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics.
Journal ArticleDOI
BrainźMachine Interface and Visual Compressive Sensing-Based Teleoperation Control of an Exoskeleton Robot
TL;DR: Considering coupled dynamics and actuator input constraints during the robot manipulation, a local adaptive fuzzy controller has been designed to drive the exoskeleton tracking the intended trajectories in human operator's mind and to provide a convenient way of dynamics compensation with minimal knowledge of the dynamics parameters of theExoskeleton robot.
Journal ArticleDOI
A review of disability EEG based wheelchair control system: Coherent taxonomy, open challenges and recommendations.
TL;DR: The background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy is determined to provide researchers and developers with a clear understanding of this platform and highlight the challenges and gaps in the current and future studies.
Journal ArticleDOI
Review of real brain-controlled wheelchairs
TL;DR: A classification is established, based on the characteristics of the BCW, such as the type of electroencephalographic signal used, the navigation system employed by the wheelchair, the task for the participants, or the metrics used to evaluate the performance, of the wheelchairs driven by a brain-computer interface.
Journal ArticleDOI
A Wireless BCI and BMI System for Wearable Robots
TL;DR: The theory of wavelet denoising method, common spatial pattern algorithm and linear discriminant analysis algorithm are investigated and the effectiveness and accuracy of these algorithms on EEG signalDenoising, feature extraction, and classification are demonstrated.
References
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