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This work proposes a Common Spatial Pattern with Polarity Check (CSPPC) to facilitate Movement Related Cortical Potential (MRCP) detection. The algorithm was compared with the Locality Preserving Projection (LPP) algorithm in the context of detecting foot dorsiflexion within a group of thirteen subjects. It has been shown that CSPPC achieved a significantly reduced delay latency compared to LPP (−25...
Hybrid Brain-Computer Interfaces (BCI) has shown great promise for neuro-prosthetics and assistive devices in the field of rehabilitation. However, the complexity involved with the system design and time cost for classification of motor tasks is a core problem when we step into clinical applications. To help address this problem, simultaneous measurements of Electroencephalography (EEG) and functional...
Kinesthetic motor imagery (KMI) tasks induce brain oscillations over specific regions of the primary motor cortex within the contralateral hemisphere of the body part involved in the process. This activity can be measured through the analysis of electroencephalographic (EEG) recordings and is particularly interesting for Brain-Computer Interface (BCI) applications. The most common approach for classification...
Decoding intended movement trajectory from neural activity is crucial for developing neuroprosthetic devices. In this study, we propose a processing framework to combine different information from two types of neural activities: action potentials (spikes) and local field potentials (LFPs). For this purpose, we proposed a stacked generalization approach based on recurrent neural network to enhance...
Visual fixation is an item of the Coma Recovery Scale-Revised (CRS-R), it is difficult to be detected by clinicians using the behavioral scales because of fluctuations of arousal level and the presence of motor impairment in disorders of consciousness (DOC) patients. Brain-computer interfaces (BCIs), which directly detect brain response without any behavioral expression, can be used to evaluate a...
The ability to allow subjects, including paralyzed patients, to perform a task using brain-computer interfaces has seen a rapid and growing success. Surprisingly, however, it is still not known how far such performance can be improved - especially in cases of long term amputation where both efferent and afferent functions are abolished and may lead to deterioration of the relevant brain representations...
In this paper, a novel electroencephalographic (EEG) based mind controlled virtual-human obstacle-avoidance platform (EEG-MC-VHOAP) is designed to improve brain computer interface (BCI) systems and offer a new game. With the EEG-MC-VHOAP, subjects can use their brain signals to control a virtual human to have a training of avoiding obstacles in a three dimensional (3D) environment. The EEG-MC-VHOAP...
Lists six panel discussion titles and their participants. A record of the panel discussions was not made available for publication as part of the conference proceedings.
Motor imagery based BCIs are one of the most important BCI paradigms. Although it has been studied for a long time, the EEG features for kinetic information of motor imagery are still less known. In this paper, we explored EEG patterns of hand force motor imagery. Six subjects participated in this study, who were required to imagine clenching their hands with two different levels of force during the...
Brain waves contain fundamental information about cortical activity: signal power within certain frequency bands, which is exploited by a variety of Brain-Computer Interface applications. For real-time systems, these features must be estimated as quickly as possible while maintaining high signal fidelity. Here, we present a statistically optimal signal processing framework for real-time bandpower...
The aim of this study is to determine the potential prognostic value of using Brain-computer Interface (BCI) to identify patients with disorder of consciousness (DOC), who show potential for recovery. A retrospective study involved 51 patients with DOC were conducted. Each patient conducted in a BCI experiment to detect awareness and received a 3-months follow-up. The BCI accuracies were correlated...
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