A concept for emotion recognition systems for children with profound intellectual and multiple disabilities based on artificial intelligence using physiological and motion signals
A concept for emotion recognition systems for children with profound intellectual and multiple disabilities based on artificial intelligence using physiological and motion signals
复制标题
基于使用生理和运动信号的人工智能的针对具有严重智力和多重障碍的儿童的情感识别系统的概念
DOI：
10.1080/17483107.2023.2170478
复制
发表时间：
2023
期刊：
影响因子：
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通讯作者：
Kuwabara Chika
中科院分区：
文献类型：
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作者：
Tanabe Hiroki;Shiraishi Toshihiko;Sato Haruhiko;Nihei Misato;Inoue Takenobu;Kuwabara Chika
PurposeThis研究提出了一个概念，情绪识别系统的儿童与深度智力和多种残疾（PIMD）的基础上人工智能（AI）使用生理和运动signals.MethodsFirst，心跳间隔（R-R间隔，RRI）的儿童PIMD的测量，和RRI和情绪之间的相关性进行了初步的实验测试。然后，使用生理和运动信号创建了基于AI的PIMD儿童情绪识别系统的概念，并使用随机森林分类器开发了基于所提出概念的情绪识别系统，该分类器将RRI，眼睛凝视和使用低物理负担传感器获取的其他数据作为输入。随后，开发的情感识别系统进行了评估，验证了所提出的概念。最后，我们提出了一个经过验证的概念，情绪recognitionsystems.ResultsA之间的相关性被发现的RRI和情绪。基于所提出的概念创建了情感识别系统并进行了测试。结果表明，“阴性”与“非阴性”的识别率为70.4% ± 6.1%（Mean ± S.D.）的情绪识别系统是高于48.5% ± 5.0%的一个不熟悉的人作为control.ConclusionThe结果表明，提出的概念，情绪识别系统是有用的沟通与儿童PIMD。
PurposeThis study proposes a concept for emotion recognition systems for children with profound intellectual and multiple disabilities (PIMD) based on artificial intelligence (AI) using physiological and motion signals.MethodsFirst, the heartbeat interval (R–R interval, RRI) of a child with PIMD was measured, and the correlation between the RRI and emotion was briefly tested in a preliminary experiment. Then, a concept based on AI for emotion recognition systems for children with PIMD was created using physiological and motion signals, and an emotion recognition system based on the proposed concept was developed using a random forest classifier taking as inputs the RRI, eye gaze, and other data acquired using low physical burden sensors. Subsequently, the developed emotion recognition system was evaluated, validating the proposed concept. Finally, we proposed a validated concept for emotion recognition systems.ResultsA correlation was found between the RRI and emotion. The emotion recognition system was created based on the proposed concept and tested. According to the results, the recognition rate of “negative” and “not negative” of 70.4% ± 6.1% (Mean ± S.D.) of the developed emotion recognition system was higher than 48.5% ± 5.0% of an unfamiliar person used as a control.ConclusionThe results indicate that the proposed concept for emotion recognition systems is useful for communicating with children with PIMD.