ArticleJournal of medical signals and sensors
Thermal Image-Based Temperament Classification by Genetic Algorithm and Adaboost Classifier.
Article in Journal of medical signals and sensors. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- See the (In)Visible: Infrared Thermography for Characterizing Thermal Patterns Associated with Peripheral Arterial Disease and Diabetes Mellitus.Medical sciences (Basel, Switzerland) · 2026Observational
- Evaluation of relationship between memory and temperament in 18-28 years old students.Caspian journal of internal medicine · 2024Article
- Assessment of the Diagnostic Methods of Mizaj in Persian Medicine: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
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Authors and funding
2 authors.
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Abstract
Background: Temperament ( Methods: The temperament of 34 participants was assessed by a PM specialist using standardized Mojahedi Mizaj Questionnaire (MMQ) and thermal images of the wrist in the supine position, the back of the hand, and their whole face under supervision of the physician were recorded. Thirteen thermal features were extracted and a classifying algorithm was designed based on the genetic algorithm and Adaboost classifier in reference to the temperament questionnaire. Results: The results showed that the mean temperature and temperature variations in the thermal images were relatively consistent with the results of MMQ. Among the three body regions, the results related to the image from Conclusions: The thermal imaging was relatively consistent with standardized MMQ and can be used as a reliable tool for evaluating warm/cold temperament. However, the results reveal that thermal imaging features may not be only main features for temperament classification and for more reliable classification, it needs to add some different features such as wrist pulse features and some subjective characteristics.
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