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We investigated whether listener-assisted scanning, an alternative communication method for persons with severe motor and visual impairments but preserved cognitive skills, could be used for spelling with EEG. To that end spoken letters were presented sequentially, and the participants made selections by performing motor execution/imagery or a cognitive task. The motor task was a brisk dorsiflexion...
This paper aims to improve tactile and bone-conduction brain computer interface (tbaBCI) classification accuracy based on a new stimulus pattern search in order to trigger more separable P300 responses. We propose and investigate three approaches to stimulus spatial and frequency content modification. As result of the online tbaBCI classification accuracy tests with six subjects we conclude that frequency...
In this study, a novel P300 based brain-computer interface (BCI) system using random set presentation pattern and employing the effect of face familiarity has been proposed and developed. While the effect of face familiarity is widely studied in the cognitive neurosciences, it has so far not been addressed for the purpose of BCI. We compare P300-based BCI performances of a conventional row-column...
In recent years, based on the steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs) have generated significant interest, due to their shorter calibration times and higher information transfer rates. Target identification is the core signal processing task in BCIs. Power spectral density analysis (PSDA) and canonical correlation analysis (CCA) are the most popular and widely...
The aim of this study is to provide a comprehensive test of head related impulse response (HRIR) for an auditory spatial speller brain-computer interface (BCI) paradigm. The study is conducted with six users in an experimental set up based on five Japanese hiragana vowels. Auditory evoked potentials resulted with encouragingly good and stable "aha-" or P300-responses in real-world online...
Noninvasive electroencephalography (EEG) brain computer interface (BCI) systems are used to investigate intended arm reaching tasks. The main goal of the work is to create a device with a control scheme that allows those with limited motor control to have more command over potential prosthetic devices. Four healthy subjects were recruited to perform various reaching tasks directed by visual cues....
In this paper, feature selection was carried out for multi-intelligence classification, and finds key regions. We designed different multi-intelligence tasks with BCI. SVM was used to classify and select features. The experiment reveals that a band has a greater effect on imagery intelligent tasks. And the introduced feature selection algorithm succeeded to detect key regions for multi-intelligence...
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