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This paper proposed a support vector machine (SVM) based classification method to identify diversified pathological voices. Sound signals were sampled from the pronunciation of a vowel "a" vocalized by 214 subjects, including 181 patients suffered from various dysphonias (such as polypoid degeneration, adductor spasmodic dysphonia, vocal fatigue, vocal(More)
OBJECTIVE Hybrid brain-computer interfaces (BCIs) have been proved to be more effective in mental control by combining another channel of physiologic control signals. Among those studies, little attention has been paid to the combined use of a steady-state visual evoked potential (SSVEP) and P300 potential, both providing the fastest and the most reliable(More)
Most EEG-based brain-computer interface (BCI) paradigms include specific electrode positions. As the structures and activities of the brain vary with each individual, contributing channels should be chosen based on original records of BCIs. Phase measurement is an important approach in EEG analyses, but seldom used for channel selections. In this paper, the(More)
Motor imagery can elicit brain oscillations in Rolandic mu rhythm and central beta rhythm, both originating in the sensorimotor cortex. In contrast with simple limb motor imagery, less work was reported about compound limb motor imagery which involves several parts of limbs. The goal of this study was to investigate the differences of the EEG patterns(More)