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Brain-Computer Interfacing [In the Spotlight
IEEE Signal Processing Magazine, 2010Recently, CNN reported on the future of brain-computer interfaces (BCIs). BCIs are devices that process a user's brain signals to allow direct communication and interaction with the environment. BCIs bypass the normal neuromuscular output pathways and rely on digital signal processing and machine learning to translate brain signals to action (Figure 1).
Rajesh P. N. Rao, Reinhold Scherer
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CeDeROM Brain Computer Interface
2012Brain Computer Interface is a biomedical equipment used to perform user interaction with computer equipment based on a brain activity measurement. Modular Research System presented in this article is a prototype platform under development aimed for supporting the research groups with low---cost versatile and flexible hardware platform for BCI research ...
Tomasz Boleslaw Cedro, Antoni Grzanka
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Brain-Computer Interfaces for Neurorehabilitation
Critical Reviews in Biomedical Engineering, 2013Brain-computer interfaces (BCIs) enable control of computers and other assistive devices, such as neuro-prostheses, which are used for communication, movement restoration, neuro-modulation, and muscle stimulation, by using only signals measured directly from the brain. A BCI creates a new output channel for the brain to a computer or a device.
Sujesh, Sreedharan +3 more
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Passive Brain–Computer Interfaces
2018Passive brain–computer interfaces (passive BCI; pBCI) have been introduced and formally defined almost a decade ago and have gained considerable attention since then. In this chapter, we clarify some points of confusion and provide a perspective on the past, present, and future of the field of passive BCI.
Krol, Laurens R. +2 more
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Beamforming in Noninvasive Brain–Computer Interfaces
IEEE Transactions on Biomedical Engineering, 2009Spatial filtering (SF) constitutes an integral part of building EEG-based brain-computer interfaces (BCIs). Algorithms frequently used for SF, such as common spatial patterns (CSPs) and independent component analysis, require labeled training data for identifying filters that provide information on a subject's intention, which renders these algorithms ...
Moritz Grosse-Wentrup +3 more
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Evolutionary Brain Computer Interfaces
2007We propose a BCI mouse and speller based on the manipulation of P300 waves in EEG signals. The 2---D motion of the pointer on the screen is controlled by directly combining the amplitudes of the output produced by a filter in the presence of different stimuli. This filter and the features to be combined within it are optimised by a GA.
Riccardo Poli +3 more
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A brain-computer interface for extended reality interfaces
ACM SIGGRAPH 2017 VR Village, 2017Extended reality (XR) technologies, such as augmented reality (AR) and virtual reality (VR), remain limited in their interaction modalities. Prevailing interaction methods such as hand gestures and voice recognition prove awkward in XR environments, even when performing common tasks (e.g., object selection, menu navigation, and others). In contrast, an
Jay Jantz, Adam Molnar, Ramses Alcaide
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Optimizing the Usability of Brain-Computer Interfaces
Neural Computation, 2018Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. An open question in the field is how to map neural activity to device movement in order to achieve the most proficient control.
Yin Zhang 0012, Steven M. Chase
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Brain–computer interfaces for communication and control
Clinical Neurophysiology, 2002For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain function might provide a new non-muscular channel for sending messages and commands to the external world - a brain-computer interface (BCI). Over the past 15 years, productive BCI research programs have arisen.
J. Wolpaw +4 more
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The Berlin Brain-Computer Interface
2008The Berlin Brain-Computer Interface (BBCI) uses a machine learning approach to extract subject-specific patterns from high-dimensional EEG-features optimized for revealing the user’s mental state. Classical BCI application are brain actuated tools for patients such as prostheses (see Section 4.1) or mental text entry systems ([2] and see [3,4,5,6] for ...
Benjamin Blankertz +7 more
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