Brain-computer Interfaces (BCIs) have been studied for nearly thirty years, with the primary motivation of providing assistive technologies for people with very severe motor disabilities. The slow speeds, high error rate, susceptibility to artifact, and complexity of BCI systems have been challenges ...
doi:10.1002/9781119144977.ch12Brain‐Computer Interfaceselementary tasksHuman‐Computer Interactioninteraction techniquesinteractive computing systemsNormantheory of actionusabilityEvain , AndéolCasiez , GryJohn Wiley & Sons, Inc.
L. G. Cohen and N. Birbaumer, "The physiology of brain-computer interfaces," J. Physiol., vol. 579, no. 3, p. 570, 2007.L.G. Cohen and N. Birbaumer, "The physiology of brain-computer interfaces," Journal of Physiology, Vol. 579(3), 570, 2007....
Brain-Computer Interfaces: Ethical and Policy Considerations 411 Ellen M. McGeeMcGee EM: Brain-computer interfaces: ethical and policy considerations. In Implantable Bioelectronics. Edited by Evgeny Katz. Weinheim, Germany: Wiley-VCH; 2014:411-433....
Brain–computer interfaces (BCIs) are a new technology that subverts traditional human–computer interaction, where the control signal source comes directly from the user’s brain. When a general BCI is used for practical applications, it is difficult for it to meet the needs of different individ...
Unlocking the potential of brain–computer interfaces (BCIs) for brain rehabilitation goes hand in hand with the remarkable power of machine learning. These intricate algorithms act as digital guides, navigating the complex landscape of brain signals to reveal the hidden pathways to recovery. By learn...
Figure 2 shows the framework proposed, in which the operator can interact with the robot manipulator through two different interfaces. The activities related to the Brain–Computer Interface are described on the left side of the figure, whereas those related to load cell and haptic control are rep...
Section 3,“Deep learning”, includes the deep learning architectures used in the literature for motor imagery brain–computer interfaces. In Section 4,“Hybrid deep learning”, we review the hybrid architectures that contain a combination of machine learning and deep learning architectures to tackle ...
brain–computer interfaces; electroencephalography; mobile EEG; rehabilitation; neurodiagnostics; motor intent detection 1. Introduction Since the early 1960s, when electroencephalography (EEG) data were first digitized and processed with a computer to today, much progress has been made in harnessing ...
brain–computer interfaces; electroencephalography; mobile EEG; rehabilitation; neurodiagnostics; motor intent detection 1. Introduction Since the early 1960s, when electroencephalography (EEG) data were first digitized and processed with a computer to today, much progress has been made in harnessing ...