Journal ArticleDOI
EEG-Based Brain-Controlled Mobile Robots: A Survey
Luzheng Bi,Xin-an Fan,Yili Liu +2 more
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TLDR
A comprehensive review of the complete systems, key techniques, and evaluation issues of brain-controlled mobile robots along with some insights into related future research and development issues is provided.Abstract:
EEG-based brain-controlled mobile robots can serve as powerful aids for severely disabled people in their daily life, especially to help them move voluntarily. In this paper, we provide a comprehensive review of the complete systems, key techniques, and evaluation issues of brain-controlled mobile robots along with some insights into related future research and development issues. We first review and classify various complete systems of brain-controlled mobile robots into two categories from the perspective of their operational modes. We then describe key techniques that are used in these brain-controlled mobile robots including the brain-computer interface techniques and shared control techniques. This description is followed by an analysis of the evaluation issues of brain-controlled mobile robots including participants, tasks and environments, and evaluation metrics. We conclude this paper with a discussion of the current challenges and future research directions.read more
Citations
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Journal ArticleDOI
Brain Computer Interface Classifiers for Semi-Autonomous Wheelchair Using Fuzzy Logic Optimization
TL;DR: The design of a hybrid BCI controller with six classifiers using an electroencephalogram (EEG) headset to detect hand motor imagery (MI) and jaw electromyography (EMG) signals is presented.
Novel Cluster-Based SVM to reduce classification error in noisy EEG data: towards real-time brain-robot interfaces
TL;DR: To be able to control a robotic platform using signals form the human brain is something that has been considered science fiction for a long time, but with the technology available today, it is possible to control such a platform using only the human mind.
Proceedings ArticleDOI
Performance Analysis of EEG Signal Processing Based Device Control Applications
TL;DR: Comparisons based on EEG signal preprocessing techniques are provided for Artificial neural networks, support vector machines, and K nearest neighbours (Knn) are used to classify works in the literature.
References
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