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Abstrakt
The automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities are used in the analyzed studies, including facial expressions, prosody of speech, and physiological signals. Regarding representation models, the basic emotions are the most frequently recognized, especially happiness, fear, and sadness. Both single-channel and multichannel approaches are applied, with a preference for the first one. For multimodal recognition, early fusion was the most frequently applied. SVM and neural networks were the most popular for building classifiers. Qualitative analysis revealed important clues on participant group construction and the most common combinations of modalities and methods. All channels are reported to be prone to some disturbance, and as a result, information on a specific symptoms of emotions might be temporarily or permanently unavailable. The challenges of proper stimuli, labelling methods, and the creation of open datasets were also identified.
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Autorzy (8)
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Ben Robins
- University of Hertfordshire
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Duygun Erol Barkana
- Yeditepe University
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Hatice Kose
- Istanbul Technical University
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Tatjana Zorcec
- University Children’s Hospital
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Nicholas Cummins
- University of Augsburg
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Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/s22041649
- Licencja
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Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach
- Opublikowano w:
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SENSORS
nr 22,
ISSN: 1424-8220 - Język:
- angielski
- Rok wydania:
- 2022
- Opis bibliograficzny:
- Landowska A., Karpus A., Zawadzka T., Robins B., Erol Barkana D., Kose H., Zorcec T., Cummins N.: Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review// SENSORS -Vol. 22,iss. 4 (2022), s.1649-
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/s22041649
- Źródła finansowania:
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- Erasmus Plus project of European Commission: EMBOA, Affective loop in Socially Assistive Robotics as an intervention tool for children with autism, contract no 2019-1-PL01- KA203-065096
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 121 razy
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