Enhancing P300-BCI performance using latency estimation
نویسندگان
چکیده
منابع مشابه
Empathy, motivation, and P300 BCI performance
Motivation moderately influences brain-computer interface (BCI) performance in healthy subjects when monetary reward is used to manipulate extrinsic motivation. However, the motivation of severely paralyzed patients, who are potentially in need for BCI, could mainly be internal and thus, an intrinsic motivator may be more powerful. Also healthy subjects who participate in BCI studies could be i...
متن کاملManipulating attention via mindfulness induction improves P300-based BCI performance
In this study, we examined the effects of a short mindfulness meditation induction (MMI) on the performance of a P300-based brain–computer interface (BCI) task. We expected that MMI would harness present moment attentional resources, resulting in two positive consequences for P300-based BCI use. Specifically, we believed MMI would facilitate increases in task accuracy and promote the production...
متن کاملClosed-looping a P300 BCI using the ErrP
The error-related potential is an event-related potential that gives information on the quality (error or correct) of what a subject observes. In this paper we try to integrate it in a P300 BCI system in order to introduce a closed-loop in this system and thus to improve its accuracy. We propose and compare different strategies of integration and discuss on their possible improvements depending...
متن کاملA Plug&Play P300 BCI Using Information Geometry
This paper presents a new classification methods for Event Related Potentials (ERP) based on an Information geometry framework. Through a new estimation of covariance matrices, this work extend the use of Riemannian geometry, which was previously limited to SMR-based BCI, to the problem of classification of ERPs. As compared to the state-of-the-art, this new method increases performance, reduce...
متن کاملEliciting dual-frequency SSVEP using a hybrid SSVEP-P300 BCI
BACKGROUND Steady-state visual-evoked potential (SSVEP)-based brain-computer interfaces (BCIs) generate weak SSVEP with a monitor and cannot use harmonic frequencies, whereas P300-based BCIs need multiple stimulation sequences. These issues can decrease the information transfer rate (ITR). NEW METHOD In this paper, we introduce a novel hybrid SSVEP-P300 speller that generates dual-frequency S...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Brain-Computer Interfaces
سال: 2017
ISSN: 2326-263X,2326-2621
DOI: 10.1080/2326263x.2017.1338010