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RISS 인기검색어
- 검색키워드
- 저자 : Benjamin Blankertz (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Ensembles of adaptive spatial filters increase BCI performance: an online evaluation
Sannelli, Claudia,Vidaurre, Carmen,Mü,ller, Klaus-Robert,Blankertz, Benjamin IOP 2016 Journal of neural engineering Vol.13 No.4
<P> <I>Objective</I>: In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain–computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. <I>Approach</I>: Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. <I>Main results</I>: The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. <I>Significance</I>: CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI inefficiency to one-fourth in comparison to previous non-adaptive paradigms.</P>
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Multiscale temporal neural dynamics predict performance in a complex sensorimotor task
Samek, Wojciech,Blythe, Duncan A.J.,Curio, Gabriel,Mü,ller, Klaus-Robert,Blankertz, Benjamin,Nikulin, Vadim V. Elsevier 2016 NeuroImage Vol.141 No.-
<P><B>Abstract</B></P> <P>Ongoing neuronal oscillations are pivotal in brain functioning and are known to influence subjects' performance. This modulation is usually studied on short time scales whilst multiple time scales are rarely considered. In our study we show that Long-Range Temporal Correlations (LRTCs) estimated from the amplitude of EEG oscillations over a range of time-scales predict performance in a complex sensorimotor task, based on Brain-Computer Interfacing (BCI). Our paradigm involved eighty subjects generating covert motor responses to dynamically changing visual cues and thus controlling a computer program through the modulation of neuronal oscillations. The neuronal dynamics were estimated with multichannel EEG. Our results show that: (a) BCI task accuracy may be predicted on the basis of LRTCs measured during the preceding training session, and (b) this result was not due to signal-to-noise ratio of the ongoing neuronal oscillations. Our results provide direct empirical evidence in addition to previous theoretical work suggesting that scale-free neuronal dynamics are important for optimal brain functioning.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Functional relevance of Long-Range Temporal Correlations (LRTCs) was investigated. </LI> <LI> LRTCs were measured with EEG during complex sensorimotor task. </LI> <LI> Alpha-band LRTCs predicted task performance. </LI> <LI> Power-law neuronal dynamics are likely to be beneficial for brain functioning. </LI> </UL> </P>
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A High-Security EEG-Based Login System with RSVP Stimuli and Dry Electrodes
Yiyu Chen,Atnafu, Ayalneh Dessalegn,Schlattner, Isabella,Weldtsadik, Wendimagegn Tariku,Myung-Cheol Roh,Hyoung Joong Kim,Seong-Whan Lee,Blankertz, Benjamin,Fazli, Siamac IEEE 2016 IEEE transactions on information forensics and sec Vol.11 No.12
<P>Lately, electroencephalography (EEG)-based authentication has received considerable attention from the scientific community. However, the limited usability of wet EEG electrodes as well as low accuracy for large numbers of users have so far prevented this new technology to become commonplace. In this study a novel EEG-based authentication system is presented, which is based on the rapid serial visual presentation paradigm and uses a knowledge-based approach for authentication. Twenty-nine subjects' data were recorded and analyzed with wet EEG electrodes as well as dry ones. A true acceptance rate of 100% can be reached for all subjects with an average required login time of 13.5 s for wet and 27 s for dry electrodes. Average false acceptance rates for the dry electrode setup were estimated to be 3.33 x 10(-5).</P>
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EEG-based usability assessment of 3D shutter glasses
Wenzel, Markus A,Schultze-Kraft, Rafael,Meinecke, Frank C,Fabien Cardinaux,Kemp, Thomas,Klaus-Robert Mü,ller,Gabriel Curio,Benjamin Blankertz IOP 2016 Journal of neural engineering Vol.13 No.1
<P> <I>Objective.</I> Neurotechnology can contribute to the usability assessment of products by providing objective measures of neural workload and can uncover usability impediments that are not consciously perceived by test persons. In this study, the neural processing effort imposed on the viewer of 3D television by shutter glasses was quantified as a function of shutter frequency. In particular, we sought to determine the critical shutter frequency at which the ‘neural flicker’ vanishes, such that visual fatigue due to this additional neural effort can be prevented by increasing the frequency of the system. <I>Approach.</I> Twenty-three participants viewed an image through 3D shutter glasses, while multichannel electroencephalogram (EEG) was recorded. In total ten shutter frequencies were employed, selected individually for each participant to cover the range below, at and above the threshold of flicker perception. The source of the neural flicker correlate was extracted using independent component analysis and the flicker impact on the visual cortex was quantified by decoding the state of the shutter from the EEG. <I>Main Result.</I> Effects of the shutter glasses were traced in the EEG up to around 67?Hz—about 20?Hz over the flicker perception threshold—and vanished at the subsequent frequency level of 77?Hz. <I>Significance.</I> The impact of the shutter glasses on the visual cortex can be detected by neurotechnology even when a flicker is not reported by the participants. <I>Potential impact.</I> Increasing the shutter frequency from the usual 50?Hz or 60?Hz to 77?Hz reduces the risk of visual fatigue and thus improves shutter-glass-based 3D usability.</P>
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