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This paper presents an algorithm for classifying single-trial electroencephalogram (EEG) during the preparation of self-paced tapping. It combines common spatial subspace decomposition with Fisher discriminant analysis to extract features from multichannel EEG. Three features are obtained based on Bereitschaftspotential and event-related desynchronization.(More)
The phytohormone auxin is important in various aspects of organism growth and development. Aux/IAA genes encoding short-lived nuclear proteins are responsive primarily to auxin induction. Despite their physiological importance, systematic analysis of Aux/IAA genes in maize have not yet been reported. In this paper, we presented the isolation and(More)
Recently, electroencephalogram-based brain-computer interfaces (BCIs) have attracted much attention in the fields of neural engineering and rehabilitation due to their noninvasiveness. However, the low communication speed of current BCI systems greatly limits their practical application. In this paper, we present a high-speed BCI based on code modulation of(More)
A brain computer interface (BCI) translates human intentions into control signals to establish a direct communication channel between the human brain and external devices. Because a BCI does not depend on the brain's normal output pathways of peripheral nerves and muscles, it can provide a new communication channel to people with severe motor disabilities.(More)
This paper introduces the development of a practical brain-computer interface at Tsinghua University. The system uses frequency-coded steady-state visual evoked potentials to determine the gaze direction of the user. To ensure more universal applicability of the system, approaches for reducing user variation on system performance have been proposed. The(More)
A motor imagery based brain-computer interface (BCI) translates the subject's motor intention into a control signal. For this BCI system, most algorithms are based on power changes of mu and beta rhythms. In this paper, we employ the measurement of phase synchrony to investigate the activities of the supplementary motor area (SMA) and primary motor area(More)
Dry and noncontact electroencephalographic (EEG) electrodes, which do not require gel or even direct scalp coupling, have been considered as an enabler of practical, real-world, brain-computer interface (BCI) platforms. This study compares wet electrodes to dry and through hair, noncontact electrodes within a steady state visual evoked potential (SSVEP) BCI(More)
PURPOSE To compare the safety and efficacy of radiofrequency ablation (RFA) and microwave ablation (MWA) in treating hepatocellular carcinoma (HCC) while conforming to the Milan criteria. MATERIALS AND METHODS The study was approved by the Institutional Review Board, and informed consent was waived due to the retrospective study design. One hundred(More)
SSVEP-based brain-computer interface (BCI) has potential advantage of high information transfer rate. However, individual difference greatly affects its practical applications. This paper presents a method of lead selection to improve the applicability of SSVEP-based BCI system. Independent component analysis (ICA) is employed to decompose EEGs over visual(More)
The posterior parietal cortex (PPC) plays an important role in motor planning and execution. Here, we investigated whether noninvasive electroencephalographic (EEG) signals recorded from the human PPC can be used to decode intended movement direction. To this end, we recorded whole-head EEG with a delayed saccade-or-reach task and found direction-related(More)