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Articles 1 - 3 of 3
Full-Text Articles in Medicine and Health Sciences
Jeffress Research Grant - 2005
Jeffress Research Grant - 2005
Virginia Journal of Science
Seven-page list of winners of the Jeffress Research Grant Awards for 2005.
Depression: Relationships To Sleep Paralysis And Other Sleep Disturbances In A Community Sample, Mariana Szklo-Coxe, Terry Young, Laurel Finn, Emmanuel Mignot
Depression: Relationships To Sleep Paralysis And Other Sleep Disturbances In A Community Sample, Mariana Szklo-Coxe, Terry Young, Laurel Finn, Emmanuel Mignot
Community & Environmental Health Faculty Publications
Sleep disturbances are important correlates of depression, with epidemiologic research heretofore focused on insomnia and sleepiness. This epidemiologic study’s aim was to investigate, in a community sample, depression’s relationships to other sleep disturbances: sleep paralysis (SP), hypnagogic/hypnopompic hallucinations (HH), cataplexy – considered rapid eye movement-related disturbances – and automatic behavior (AB). Although typical of narcolepsy, these disturbances are prevalent, albeit under-studied, in the population. Cross-sectional analyses (1998–2002), based on Wisconsin Sleep Cohort Study population-based data from 866 participants (mean age 54, 53% male), examined: depression (Zung Self-Rating Depression Scale), trait anxiety (Spielberger State-Trait Anxiety Inventory, STAI-T ≥ 75th percentile), and …
Exploration Of Computational Methods For Classification Of Movement Intention During Human Voluntary Movement From Single Trial Eeg, Ou Bai, Peter Lin, Sherry Vorbach, Jiang Li, Steve Furlani, Mark Hallett
Exploration Of Computational Methods For Classification Of Movement Intention During Human Voluntary Movement From Single Trial Eeg, Ou Bai, Peter Lin, Sherry Vorbach, Jiang Li, Steve Furlani, Mark Hallett
Electrical & Computer Engineering Faculty Publications
Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG).
Methods: Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis …