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، جلد ۱۱، شماره ۲، صفحات ۲۶۵-۲۷۷
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Evaluation of Eye-Blinking Dynamics in Human Emotion Recognition using Weighted Visibility Graph |
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| چکیده انگلیسی مقاله |
Currently, designing an automated emotion recognition system using biosignals becomes a hot and challenging issue in many fields, including human-computer interferences, robotics, and affective computing. Several algorithms have been proposed to characterize the internal and external behaviors of the subjects in confronting emotional events/stimuli. Eye movements, as an external behavior, are habitually analyzed in a multi-modality system using classic statistical measures, and the evaluation of its dynamics has been neglected so far. This experiment intended to provide an innovative single-modality scheme for emotion classification using eye-blinking data. For the first time, the dynamics of eye-blinking data have been characterized by weighted visibility graph-based indices. The extracted measures were then fed to the different classifiers, including support vector machine, decision tree, k-Nearest neighbor, AdaBoost, and random subset, to complete the process of classification. The proposed framework provided significant performance in terms of recognition rates. The highest average recognition rates of > 90% were achieved using the decision tree. In brief, our results showed that eye-blinking data has the potential for emotion recognition. The present system can be extended for designing future affect recognition systems. |
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| کلیدواژه‌های انگلیسی مقاله |
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| نویسندگان مقاله |
| Atefeh Goshvarpour
Department of Biomedical Engineering, Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.
| Ateke Goshvarpour
Department of Biomedical Engineering, Imam Reza International University, Mashhad, Razavi Khorasan, Iran
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| نشانی اینترنتی |
https://fbt.tums.ac.ir/index.php/fbt/article/view/566 |
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