How many people are able to operate an EEG-based brain-computer interface (BCI)?

By Christoph Guger, G. Edlinger, W. Harkam, I. Niedermayer, Gert Pfurtscheller. IEEE transactions on neural systems and rehabilitation engineering, 2003

561 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/d8c87498adbcb9b2ad1655f63f52a2130fe2aa3b

How researchers see this paper

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

In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

Brain-Computer Interfaces: A Gentle Introduction (2009, background): “Furthermore, a minority of subjects exhibit little or no control [11, 26, 31, ].”
Toward Unsupervised Adaptation of LDA for Brain–Computer Interfaces (2011, background): “In [17]–[19], they described a P300-based BCI system, which uses a different type of features that are more stationary (cf., [ 20 ] and [21]) than those obtained by motor imagery, and therefore, the system poses different challenges.”
Brain-computer interface technology: a review of the Second International Meeting. (2003, unknown): “For all these issues, large-scale studies are important [50].”
EEG datasets for motor imagery brain–computer interface (2017, unknown): “This is greater than a report on 99 subjects [21] showing that 6.7% of the subjects had accuracies lower than 60% (here,”
P300 brain computer interface: current challenges and emerging trends (2012, methodology): “A similar study using a MI BCI with N = 99 subjects showed that only 19% of the subjects were able to achieve an accuracy of 80–100% (Guger et al., 2003).”
Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges (2010, background): “This is a big step forward in BCI research, because at least 25–30% of all users are not able to use a BCI with sufficient level of control (Guger et al., 2003).”
An MEG-based brain-computer interface (BCI) (2007, methodology): “Histogram of typical EEG on-line classification accuracies over 40 trials after 20–30 min training time (data from Guger et al. (2003), Table 2, sum of session counts computed from third and fifth column).”
EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy (2019, unknown): “The classification results of all three paradigms resulted in performances that are comparable to those of previous BCI studies [8,21,35,52,53].”
Could Anyone Use a BCI? (2010, background): “Authors have described subjects’ unacceptable performance as “bad” (Cheng et al. 2002), “marginal” ( Guger et al. 2003 ), “low” (Allison et al. 2008) or “poor” (Leeb et al. 2007).”
Short-term emotion assessment in a recall paradigm (2009, background): “In (Guger et al., 2003) the authors showed that around 75% of the 99 untrained participants that took part in a two class BCI paradigm without feedback obtained accuracies between 60% and 79%.”
Single-trial analysis and classification of ERP components - A tutorial (2011, unknown): “However, regardless of the particular techniques employed for feature extraction or classification, there is substantial variability in the classification accuracy both between subjects [26, 7, 30, 25, 17, 1] and within subjects during the course of an experiment [62].”
Steady-state somatosensory evoked potentials: suitable brain signals for brain-computer interfaces? (2006, background): “In fact, movement imagination is an active mental process and not everybody is able to perform this task [5].”
Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation (2019, background): “It is necessary to mention that another issue often related to the use of brain signals to drive external devices is the need of extensive training [105,106] and poor performances of the brain to computer interface.”
BCI Demographics: How Many (and What Kinds of) People Can Use an SSVEP BCI? (2010, background): “ance as to why some subjects were better than others [20].”
The Berlin Brain-Computer Interface: Accurate performance from first-session in BCI-naive subjects (2008, methodology): “To date, the only study that investigates BCI feedback accuracy on a larger subject population is [14].”