Detecting emotional reactions to videos of depression

被引:8
作者
Zhu, Xuanying [1 ]
Gedeon, Tom [1 ]
Caldwell, Sabrina [1 ]
Jones, Richard [1 ]
机构
[1] Australian Natl Univ, Res Sch Comp Sci, Canberra, ACT, Australia
来源
2019 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES 2019) | 2019年
关键词
Depression Detection; Physiological Signals; Galvanic Skin Response; Skin Temperature; Pupil Dilation; SUICIDE;
D O I
10.1109/ines46365.2019.9109519
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We can physically sense depression in others, and this recognition can be detected by using neural networks to analyse our physiological responses to observing individuals with depression. The behaviour of 16 individuals suffering from various levels depression were shown in short videos to 12 experiment participants (observers) whose physiological signals we recorded. Consciously, depression is not normally interesting, so does not provoke strong conscious recognition, and hence barely over chance, at 27%. However, at emotional levels, depression is interesting, so provokes physiological reactions we can measure, leading to neural network classification of 92%.
引用
收藏
页码:147 / 152
页数:6
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