Suchergebnisse - "Brain-Computer Interfaces/classification"

Adaptive transfer learning for EEG motor imagery classification with deep Convolutional Neural Network von Zhang, Kaishuo, Robinson, Neethu, Lee, Seong-Whan, Guan, Cuntai

“… In recent years, deep learning has emerged as a powerful tool for developing Brain–Computer Interface (BCI) systems. However, for deep learning models trained …”
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A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives von Choi, Inchul, Rhiu, Ilsun, Lee, Yushin, Yun, Myung Hwan, Nam, Chang S.

“… A new Brain-Computer Interface (BCI) technique, which is called a hybrid BCI, has recently been proposed to address the limitations of conventional single BCI …”
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Data augmentation for self-paced motor imagery classification with C-LSTM von Freer, Daniel, Yang, Guang-Zhong

“… Objective. Brain-computer interfaces (BCI) are becoming important tools for assistive technology, particularly through the use of motor imagery (MI) for aiding …”
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Double ErrP Detection for Automatic Error Correction in an ERP-Based BCI Speller von Cruz, Aniana, Pires, Gabriel, Nunes, Urbano J.

“… Brain-computer interface (BCI) is a useful device for people with severe motor disabilities. However, due to its low speed and low reliability, BCI still has a …”
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Classification of different reaching movements from the same limb using EEG von Shiman, Farid, López-Larraz, Eduardo, Sarasola-Sanz, Andrea, Irastorza-Landa, Nerea, Spüler, Martin, Birbaumer, Niels, Ramos-Murguialday, Ander

“… Objective. Brain-computer-interfaces (BCIs) have been proposed not only as assistive technologies but also as rehabilitation tools for lost functions. However, …”
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Classification of Individual Finger Movements Using Intracortical Recordings in Human Motor Cortex von Jorge, Ahmed, Royston, Dylan A, Tyler-Kabara, Elizabeth C, Boninger, Michael L, Collinger, Jennifer L

“… Abstract BACKGROUND Intracortical microelectrode arrays have enabled people with tetraplegia to use a brain–computer interface for reaching and grasping. In …”
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Pure visual imagery as a potential approach to achieve three classes of control for implementation of BCI in non-motor disorders von Sousa, Teresa, Amaral, Carlos, Andrade, João, Pires, Gabriel, Nunes, Urbano J, Castelo-Branco, Miguel

“… The achievement of multiple instances of control with the same type of mental strategy represents a way to improve flexibility of brain-computer interface …”
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Integrating language models into classifiers for BCI communication: a review von Speier, W, Arnold, C, Pouratian, N

“… The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication …”
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Weighted spatial based geometric scheme as an efficient algorithm for analyzing single-trial EEGS to improve cue-based BCI classification von Alimardani, Fatemeh, Boostani, Reza, Blankertz, Benjamin

“… There is a growing interest in analyzing the geometrical behavior of electroencephalogram (EEG) covariance matrix in the context of brain computer interface …”
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A Multi-Class Tactile Brain-Computer Interface Based on Stimulus-Induced Oscillatory Dynamics von Yao, Lin, Chen, Mei Lin, Sheng, Xinjun, Mrachacz-Kersting, Natalie, Zhu, Xiangyang, Farina, Dario, Jiang, Ning

“… We proposed a multi-class tactile brain-computer interface that utilizes stimulus-induced oscillatory dynamics. It was hypothesized that somatosensory …”
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Sparse representation-based classification scheme for motor imagery-based brain-computer interface systems von Shin, Younghak, Lee, Seungchan, Lee, Junho, Lee, Heung-No

“… Motor imagery (MI)-based brain-computer interface systems (BCIs) normally use a powerful spatial filtering and classification method to maximize their …”
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Invariance and variability in interaction error-related potentials and their consequences for classification von Abu-Alqumsan, Mohammad, Kapeller, Christoph, Hintermüller, Christoph, Guger, Christoph, Peer, Angelika

“… This paper discusses the invariance and variability in interaction error-related potentials (ErrPs), where a special focus is laid upon the factors of (1) the …”
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A hybrid three-class brain-computer interface system utilizing SSSEPs and transient ERPs von Breitwieser, Christian, Pokorny, Christoph, Müller-Putz, Gernot R

“… This paper investigates the fusion of steady-state somatosensory evoked potentials (SSSEPs) and transient event-related potentials (tERPs), evoked through …”
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Self-recalibrating classifiers for intracortical brain-computer interfaces von Bishop, William, Chestek, Cynthia C, Gilja, Vikash, Nuyujukian, Paul, Foster, Justin D, Ryu, Stephen I, Shenoy, Krishna V, Yu, Byron M

“… Intracortical brain-computer interface (BCI) decoders are typically retrained daily to maintain stable performance. Self-recalibrating decoders aim to remove …”
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Covert Verb Reading Contributes to Signal Classification of Motor Imagery in BCI von Zhang, Hong, Sun, Yaoru, Li, Jie, Wang, Fang, Wang, Zijian

“… Motor imagery is widely used in the brain-computer interface (BCI) systems that can help people actively control devices to directly communicate with the …”
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Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase von Zink, Rob, Hunyadi, Borbála, Huffel, Sabine Van, Vos, Maarten De

“… One of the major drawbacks in EEG brain-computer interfaces (BCI) is the need for subject-specific training of the classifier. By removing the need for a …”
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A comparison of classification techniques for a gaze-independent P300-based brain-computer interface von Aloise, F, Schettini, F, Aricò, P, Salinari, S, Babiloni, F, Cincotti, F

“… This off-line study aims to assess the performance of five classifiers commonly used in the brain-computer interface (BCI) community, when applied to a …”
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Classifier-based latency estimation: a novel way to estimate and predict BCI accuracy von Thompson, David E, Warschausky, Seth, Huggins, Jane E

“… Brain-computer interfaces (BCIs) that detect event-related potentials (ERPs) rely on classification schemes that are vulnerable to latency jitter, a phenomenon …”
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Discriminative Methods for Classification of Asynchronous Imaginary Motor Tasks From EEG Data von Delgado Saa, Jaime F., Cetin, Mujdat

“… In this work, two methods based on statistical models that take into account the temporal changes in the electroencephalographic (EEG) signal are proposed for …”
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Employing an active mental task to enhance the performance of auditory attention-based brain–computer interfaces von Xu, Honglai, Zhang, Dan, Ouyang, Minhui, Hong, Bo

“… ► The active mental task (AMT) generated a stronger late positive ERP response other than the P300 evoked by a traditional oddball counting paradigm. ► The AMT …”
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