Facial expression recognition and emotional regulation in narcolepsy with cataplexy
نویسندگان
چکیده
منابع مشابه
Cataplexy Emotional Trigger Questionnaire (CETQ)--a brief patient screen to identify cataplexy in patients with narcolepsy.
STUDY OBJECTIVES This pilot study explored the sensitivity and specificity of a brief survey to determine the presence of cataplexy. We hypothesized that the brief questionnaire could provide a quick, sensitive, and specific screening tool to identify those patients with cataplexy, which would result in more timely referrals for further diagnostic testing. DESIGN The pilot study utilized a br...
متن کاملFacial Expression Recognition Based on Structural Changes in Facial Skin
Facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. In recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. As machine vision and artificial intelligence advan...
متن کاملNarcolepsy and Cataplexy
After hearing the punch line of the joke, the teenager falls to the floor, almost as if actually punched. She remains there, completely unable to move. She hears her parents reassure her friends that they need not worry about her because she will be all right in a few minutes. She is embarrassed and frustrated as the episode continues, and her friends begin to leave. They bid her goodbye, but s...
متن کاملNarcolepsy and Cataplexy
Epidemiology [3] Prevalence is estimated as 25 per 100,000 in Caucasian populations. [4] Age of onset is typically around adolescence. A smaller number of cases presents at around 35 years. Less than 5% of narcolepsy with cataplexy occurs in children. One study found that it was often linked to complex movement disorders. [5] It is possible that incidence statistics would increase if diagnostic...
متن کاملHuman Emotional Facial Expression Recognition
An automatic Facial Expression Recognition (FER) model with Adaboost face detector, feature selection based on manifold learning and synergetic prototype based classifier has been proposed. Improved feature selection method and proposed classifier can achieve favorable effectiveness to performance FER in reasonable processing time.
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ژورنال
عنوان ژورنال: Journal of Sleep Research
سال: 2012
ISSN: 0962-1105
DOI: 10.1111/jsr.12002