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Brain-computer interface (BCI) plays an important role in helping the people with severe motor disability. In event-related potential (ERP) based BCIs, subjects were asked to count the target stimulus in the offline experiment, the recorded electroencephalogram (EEG) data was used to train the classification mode. However, subjects may make mistakes in counting the target stimulus or be affected by...
Until now, the canonical correlation analysis (CCA)-based method has been most widely applied to steady-state visual evoked potential (SSVEP). Artificial sine-cosine signals are used as the original references in the CCA method, which could hardly reflect the real SSVEP features buried in electroencephalogram (EEG). In this study, we use principal component analysis (PCA) to extract EEG features multivariate...
This paper presents a brain-computer interface (BCI) in which the face paradigm was optimized for the visual mismatch negativity (MMN). There were 12 cells in a LCD monitor. A single letter was at the bottom of each cell. In the new paradigm, a color face appeared above each of the 12 cells randomly while the gray faces appeared in others 11 cells. A traditional face paradigm with single character...
Up to 30% of epileptic patients have seizures poorly controlled with anti-epileptic drugs alone. Surgical therapy might be beneficial to patients who respond poorly to drug treatments. It is therefore crucial to accurately localize the seizure focus. Neurologists rely heavily on seizures to determine the focus. The invasive recordings usually continue for days or weeks, which is costly and entails...
Detection of interictal discharges is a key element of interpreting EEGs during the diagnosis and management of epilepsy. Because interpretation of clinical EEG data is time-intensive and reliant on experts who are in short supply, there is a great need for automated spike detectors. However, attempts to develop general-purpose spike detectors have so far been severely limited by a lack of expert-annotated...
Most of the existed methods for steady-state visual evoked potential (SSVEP) recognition require a specified time window length (TWL) to estimate the dominant frequency components in EEG signals. Typically, the TWL is manually predetermined and then fixed during running of the SSVEP-based brain-computer interface (BCI), which may not give the optimal information transfer rate (ITR). This study proposes...
In this paper, an experiment was designed to record the electroencephalography when people caught the vision of differently directional moving (turning right, turning left, moving forward, moving backward). The signals from 30 EEG channels were analyzed by independent component analysis to obtain the independent components. The tagged permutations of independent components were obtained and a discrete...
An experiment was designed to record the electroencephalography (EEG) when people caught the vision of different directional moving (turning right, turning left, moving forward, moving backward). The EEG signals were obtained from 30 EEG electrode sites. The tagged permutations of EEG electrode sites were obtained and a discrete space was formed by the tags. DPSO algorithm was used to search the optimal...
An experiment was designed to record the electroencephalography, when people caught the vision of different directional moving. Independent components analysis was used to analyze the EEG signal. The selection of independent component has received a great deal of attention in the field of signal processing and image processing. Here, F-score of multisets was used to select the valuable independent...
In this paper, an experiment was designed to get the electroencephalography (EEG) when people caught the vision of moving to different direction (right, left, front, back). Through Fourier Transform., the feature of the EEG was obtained. Then, the algorithm of principal component analysis (PCA) was used to simplify the feature. Finally, in order to classify the direction perception EEG, it was distinguished...
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