Takamasa Shimada

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In psychiatry, the sleep stage is one of the most important evidence for diagnosing mental disease. However, doctors require much labor and skill for diagnosis, so a quantitative and objective method is required for more accurate diagnosis since it depends on the doctor's experience. For this reason, an automatic diagnosis system must be developed. In this(More)
Telemedicine can be implemented using a sensor network that carries users’ biometric information collected by tiny intelligent sensors attached to the human body. We propose a communication system that can be used for telemedicine to improve the Quality of Life of individuals, which uses a sensor network and a sensor database with mutual(More)
In this study, we have improved upon the P300 speller Brain-Computer Interface paradigm by introducing a new character encoding method. Our concept in detection of the intended character is not based on a classification of target and nontarget responses, but based on an identifaction of the character which maximize the difference between P300 amplitudes in(More)
We propose a simple character identification method demonstrated by using an electroencephalogram (EEG) with a stimulus presentation technique. The method assigns a code maximizing the minimum Hamming distance between character codes. Character identification is achieved by increasing the difference between target and non-target responses without(More)
In the current study, we quantitatively evaluated aging and schizophrenia using statistical indices reflecting enhancement and suppression at arbitrary frequencies using photic stimulation (PS). This index corresponds to the Z-score, which reflects the distance between two amplitude distributions at an arbitrary frequency at rest and during PS. We measured(More)
In this paper, we propose a method to acquire temporal changes of activations by moving an analysis time window. An advantage of this method is that it can acquire rough changes of activated areas even with the data having low time resolution. We ascertained that activations from our method do not contradict previous reports on the oddball paradigm, thus(More)
In the current study, we tested a proposed method for fast spike detection using a general-purpose computer. First, we performed eigenvalue analysis using a gradient calculated from two neighboring samples to detect high-amplitude negative peaks. Clustering was performed to classify detected peaks by considering amplitude distribution at scalp electrodes.(More)
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