A brain-computer interface (BCI) translates the brain activity into commands to control external devices. P300 speller based character recognition is an important kind of application system in BCI. In this paper, we propose a framework to integrate channel correlation analysis into P300 detection. This work is distinguished by two key contributions. First, a coefficient matrix is introduced and constructed for multiple channels with the elements indicating channel correlations. Agglomerative clustering is applied to group correlated channels. Second, the statistics of central tendency are used to fuse the information of correlated channels and generate virtual channels. The generated virtual channels can extend the EEG signals and lift up the signal-to-noise ratio. The correlated features from virtual channels are combined with original signals for classification and the outputs of discriminative classifier are used to determine the characters for spelling. Experimental results prove the effectiveness and efficiency of the channel correlation analysis based framework. Compared with the state-of-the-art, the recognition rate was increased by both 6% with 5 and 10 epochs by the proposed framework.

In this letter, a new concept of life log retrieval using human brain activities is presented. The non-invasive electroencephalogram (EEG) recording was applied to have P300 evoked potentials during the photo retrieving tasks. Three subjects tried to select the photo images that interest them among nine according to their mental states. It was found that with four times EEG averaging, the performances of target photo selections could reach 90% for two subjects. This concept would be applicable in future to achieve intuitive retrieval of life log with large quantities of data.

Using event-related potential (P300 and CNV), the cognitive function of elderly subjects was compared with that of young subjects. It was found that the prolonged cognitive information processing induced by aging was reflected in the P300 and N400 latency. The effects of aging were not observed in the P300 amplitude. The CNV measurements, in the range of this study, did not reflect the effects of aging. This might be because the CNV reflects a higher cognitive function as compared with P300 and the effects of aging do not appear in such a function. The data also suggested that the cognitive style must be taken into account when evaluating the deterioration of cognitive functions with aging.