Electronics · 2021 · 53 citations · 189 references
EngineeringBiomedical EngineeringComputer ScienceAutomationHuman-computer InteractionNeural EngineeringBrain-computer InterfacesHuman-machine InteractionHuman-machine InterfacesNeural InterfacesNeural Signal AcquisitionNeural Signal ProcessingAlertnessBrain-computer Interface EthicsBrain-computer Interface Signal AcquisitionBrain-computer Interface Signal AnalysisBrain-computer Interface Signal ProcessingBrain-machine InterfacesData Privacy RequirementsLie Detection
Brain–computer interfaces, once a speculative concept, are now emerging through advances in biomedical engineering, computer science, and neuroscience, with applications ranging from security and lie detection to gaming, education, art, and cognitive augmentation. This tutorial surveys the main features and challenges of brain–computer interfaces—signal acquisition, filtering, processing, ethics, privacy, and performance assessment—to inform students, researchers, and practitioners. The tutorial reviews key components—signal acquisition, filtering, processing, ethical considerations, data privacy, and performance metrics—within biomedical and automation engineering contexts.
The prospect and potentiality of interfacing minds with machines has long captured human imagination. Recent advances in biomedical engineering, computer science, and neuroscience are making brain–computer interfaces a reality, paving the way to restoring and potentially augmenting human physical and mental capabilities. Applications of brain–computer interfaces are being explored in applications as diverse as security, lie detection, alertness monitoring, gaming, education, art, and human cognition augmentation. The present tutorial aims to survey the principal features and challenges of brain–computer interfaces (such as reliable acquisition of brain signals, filtering and processing of the acquired brainwaves, ethical and legal issues related to brain–computer interface (BCI), data privacy, and performance assessment) with special emphasis to biomedical engineering and automation engineering applications. The content of this paper is aimed at students, researchers, and practitioners to glimpse the multifaceted world of brain–computer interfacing.
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RELATIONS BETWEEN TWO SETS OF VARIATES
Harold Hotelling · Biometrika · 1936 · 5.4K citations
Motor imagery and direct brain-computer communication
G. Pfurtscheller, Christa Neuper · Proceedings of the IEEE · 2001 · 1.9K citations