Bio-Visual Fusion for Person-Independent Recognition of Pain Intensity

被引:42
作者
Kaechele, Markus [1 ]
Werner, Philipp [2 ]
Al-Hamadi, Ayoub [2 ]
Palm, Guenther [1 ]
Walter, Steffen [3 ]
Schwenker, Friedhelm [1 ]
机构
[1] Univ Ulm, Inst Neural Informat Proc, D-89069 Ulm, Germany
[2] Univ Magdeburg, Inst Informat Technol, D-39106 Magdeburg, Germany
[3] Univ Ulm, Dept Psychosomat Med & Psychotherapy, D-89069 Ulm, Germany
来源
MULTIPLE CLASSIFIER SYSTEMS (MCS 2015) | 2015年 / 9132卷
关键词
D O I
10.1007/978-3-319-20248-8_19
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this work, multi-modal fusion of video and biopotential signals is used to recognize pain in a person-independent scenario. For this purpose, participants were subjected to painful heat stimuli under controlled conditions. Subsequently, a multitude of features have been extracted from the available modalities. Experimental validation suggests that the cues that allow the successful recognition of pain are highly similar across different people and complementary in the analysed modalities to an extent that fusion methods are able to achieve an improvement over single modalities. Different fusion approaches (early, late, trainable) are compared on a large set of state-of-the art features for the biopotentials and video channels in multiple classification experiments.
引用
收藏
页码:220 / 230
页数:11
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