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ID 118009
著者
Akiyama, Toshiya Tokushima University
Tanioka, Ryuichi Hiroshima Cosmopolitan University
Betriana, Feni Rozzano Locsin Institute
Zhao, Yueren Fujita Health University
Kai, Yoshihiro Tokai University
宮川, 操 Tokushima Bunri University
Soriano, Gil National University Philippines
キーワード
facial emotion recognition
human–robot interaction
multi-task cascaded convolutional networks
reliability
patients with schizophrenia
healthy participants
資料タイプ
学術雑誌論文
抄録
Patients with schizophrenia may exhibit a flat affect and poor facial expressions. This study aimed to compare subjective facial emotion recognition (FER) and FER based on multi-task cascaded convolutional network (MTCNN) face detection in 31 patients with schizophrenia (patient group) and 40 healthy participants (healthy participant group). A Pepper Robot was used to converse with the 71 aforementioned participants; these conversations were recorded on video. Subjective FER (assigned by medical experts based on video recordings) and FER based on MTCNN face detection was used to understand facial expressions during conversations. This study confirmed the discriminant accuracy of the FER based on MTCNN face detection. The analysis of the smiles of healthy participants revealed that the kappa coefficients of subjective FER (by six examiners) and FER based on MTCNN face detection concurred (κ = 0.63). The perfect agreement rate between the subjective FER (by three medical experts) and FER based on MTCNN face detection in the patient, and healthy participant groups were analyzed using Fisher’s exact probability test where no significant difference was observed (p = 0.72). The validity and reliability were assessed by comparing the subjective FER and FER based on MTCNN face detection. The reliability coefficient of FER based on MTCNN face detection was low for both the patient and healthy participant groups.
掲載誌名
Healthcare
ISSN
22279032
出版者
MDPI
10
12
開始ページ
2363
発行日
2022-11-24
権利情報
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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言語
eng
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出版社版
部局
理工学系
医学系