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In recent years, emotion classification from electroencephalogram (EEG) has attracted more and more attention. Because fewer channels were required in the real-time emotion classification system, many channel selection methods were proposed. In this paper, we investigated the stability of the optimal channels selected by channel selection algorithm, Mean-ReliefF-channel-selection (MRCS). EEG signals...
Electroencephalogram (EEG) plays an important role in E-healthcare systems, especially in the mental healthcare area, where constant and unobtrusive monitoring is desirable. In the context of OPTIMI project, a novel, low cost, and light weight wearable EEG sensor has been designed and produced. In order to improve the performance and reliability of EEG sensors in real-life settings, we propose a method...
There have been a number of research projects which have addressed depression, the focus often being on aspects of pharmacology and psychology. Relatively few of the investigations have tried to integrate depression and the related issues into a pervasive depression prevention system incorporating user-centered design. In this paper we propose an approach to provide relief for a user(s) depression...
Mental health care is becoming an increasing concern in home care projects. As an integral part of Telecare and Telehealth systems, portable EEG recording and real-time analysis are increasingly being used as non-intrusive monitoring techniques. In home environments without the supervision of a physician and absence of electromagnetic shielding, the raw EEG data, especially the most important alpha...
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