Cluster analytic detection of disgust-arousal
MetadataShow full item record
Automated detection of disgust-arousal could have applications in diagnosing and treating obsessive-compulsive disorder and Huntington's disease. For achieving this ability, experimental data was used first to examine the thermal response of "facial muscles of disgust" to other common negative and positive expressions of emotive states. An attempt was then made to detect disgust-arousal through classification of affect-educed thermal variations measured along the facial muscles. Initial results suggest (i) muscles of disgust experience different levels of thermal variations under the influence of various emotive state and (ii) emotion-educed facial thermal patterns can be modeled as stochastically independent clusters to be separated as linear spaces and making automated detection of disgust-arousal possible. © 2009 IEEE.
Showing items related by title, author, creator and subject.
Khan, Masood Mehmood (2009)Automated detection of disgust-arousal could have applications in diagnosing and treating obsessive-compulsive disorder and Huntington’s disease. For achieving this ability, experimental data was used first to examine the ...
Khan, Masood Mehmood; Ward, R.; Ingleby, M. (2016)Automated assessment of affect and arousal level can help psychologists and psychiatrists in clinical diagnoses; and may enable affect-aware robot-human interaction. This work identifies major difficulties in automating ...
Classifying pretended and evoked facial expressions of positive and negative affective states using infrared measurement of skin temperatureKhan, Masood Mehmood; Ward, R. D.; Ingleby, M. (2009)Earlier researchers were able to extract the transient facial thermal features from thermal infrared images (TIRIs) to make binary distinctions between the expressions of affective states. However, effective human-computer ...