用多模态情绪检测支持抑郁症筛查

R. Francese, Pasquale Attanasio
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引用次数: 6

摘要

抑郁症是意大利人群中最常见的精神障碍。贝克抑郁量表ii (BDI-II)是临床医生普遍采用的抑郁指标。在本文中,我们提出了LieToMe,一个旨在收集BDI-II患者的答案以及她的图像和声音的移动应用程序。利用深度卷积神经网络对视频和图像进行情感分析。情绪结果与患者DBI-II评分之间的相关性提供给临床医生,作为患者情绪状态与抑郁症筛查结果之间关系的指示。我们进行初步评估,旨在评估临床医生对lieetome提供的支持的满意度。参与者为8名临床医生。结果似乎支持LieToMe在临床实践中的可接受性。
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Supporting Depression Screening with Multimodal Emotion Detection
Depression is the most common mental disorder in Italian population. The Beck Depression Inventory-II (BDI-II) questionnaire is generally adopted by clinicians as indicator of depression. In this paper we propose LieToMe, a mobile application aiming at collecting together with the BDI-II patient’s answers also her images and voice. Emotional analysis is performed on the video and on the images by using deep Convolutional Neural Network. The correlation between the emotional results and the patient’s DBI-II scores is provided to the clinician as indication of the relationship between the patient’s emotional state and the result of the depression screening. We conduct a preliminary evaluation aiming at assessing the clinician satisfaction on the support offered by LieToMe . Participants were 8 clinicians. Results seem to support the acceptability of LieToMe in the clinical practice.
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