Brain-Computer Interfaces: Principles and Practice

By Jonathan R. Wolpaw, E. Wolpaw. 2012

908 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/955e2d6b7f237add6cde6b9786efbb7d9ef6893a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update (2018, methodology): “In particular, the main challenges faced by classification methods for BCI are the low signal-to-noise ratio of EEG signals [172, 228], their non-stationarity over time, within or between users, where same-user EEG signals varying between or even within runs [202, 80, 109, 164, 145, 56], the limited”
Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface (2015, background): “Brain-computer interfaces (BCIs) aim to provide a richer, more powerful command signal for assistive devices by decoding movement intentions in real time directly from neural activity ( 1 – 3 ).”
Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review (2017, unknown): “Over the past 15 years the BCI field has grown considerably thanks to substantial granting by the EC in Europe and by the NIH and NSF in the USA, among others, becoming the most prominent applied research area for EEG as a whole [2-5].”
On the interpretation of weight vectors of linear models in multivariate neuroimaging (2014, background): “In other applications such as brain – computer interfacing (BCI, Dornhege et al., 2007; Wolpaw & Wolpaw, 2012), researchers are mainly interested in estimating (or decoding) brain states from neuroimaging data, or vice versa.”
Signal Processing Approaches to Minimize or Suppress Calibration Time in Oscillatory Activity-Based Brain–Computer Interfaces (2015, background): “Brain–computer interfaces (BCI) are systems that enable their users to interact with a computer by means of brain activity only, this activity being typically measured by electroencephalography (EEG) [1].”
Riemannian Approaches in Brain-Computer Interfaces: A Review (2017, unknown): “widely used is their low robustness and reliability [1], [7].”
Brain-computer interfaces in medicine. (2012, background): “Functional magnetic resonance imaging (fMRI) and functional near-infrared imaging (fNIR) measure the blood oxygenation of a cerebral region and correlate with neural activity.(1) Lee et al(20) demonstrated that control of a robotic arm only through the person’s thought processes was possible using a”
EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications (2020, background): “Later, a formal definition of the term ’BCI’ was interpreted as a direct communication pathway between the human brain and an external device [3].”
Brain–Computer Interface Spellers: A Review (2018, methodology): “Accordingly, this paradigm consists of three main prerequisites [6]:”
BCILAB: a platform for brain–computer interface development (2013, background): “According to a recent deﬁnition [10], ‘a brain–computer interface, or BCI, is a system that measures central nervous system (CNS) activity and converts it into artiﬁcial output that replaces, restores, enhances, supplements, or improves natural CNS output, and thereby changes the ongoing…”