生理信号情感特征提取工具箱

Q1 Computer Science
M. Soleymani, Frank Villaro-Dixon, T. Pun, G. Chanel
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引用次数: 59

摘要

生理反应是情绪发作的重要组成部分。本文介绍了一个生理信号情感特征提取工具箱(TEAP)。这个开源工具箱可以预处理和计算多个生理信号的情感相关特征,即脑电图(EEG)、皮肤电反应(GSR)、肌电图(EMG)、皮肤温度、呼吸模式和血容量脉搏。这个工具箱中的特性在两个公开可用的数据库(即MAHNOB-HCI和DEAP)上进行了测试。我们演示了使用这个工具箱中的特性可以实现与原始工作相似的性能。该工具箱是在MATLAB中实现的,也与Octave兼容。我们希望这个工具箱能进一步发展,加速情感生理信号分析的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toolbox for Emotional feAture extraction from Physiological signals (TEAP)
Physiological response is an important component of an emotional episode. In this paper, we introduce a Toolbox for Emotional feAture Extraction from Physiological signals (TEAP). This open source toolbox can preprocess and calculate emotionally relevant features from multiple physiological signals, namely, electroencephalogram (EEG), galvanic skin response (GSR), electromyogram (EMG), skin temperature, respiration pattern and blood volume pulse. The features from this toolbox are tested on two publicly available databases, i.e., MAHNOB-HCI and DEAP. We demonstrated that we achieve similar performance to the original work with the features from this toolbox. The toolbox is implemented in MATLAB and is also compatible with Octave. We hope this toolbox to be further developed and accelerate research in affective physiological signal analysis.
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来源期刊
Frontiers in ICT
Frontiers in ICT Computer Science-Computer Networks and Communications
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