AIMC Topic: Arousal

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Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolution Neural Network.

Studies in health technology and informatics
Automated emotion recognition plays a vital role in problem solving, decision making and social activities of human life. An emotion is a set of reactions and experience to a given conditions, which are modeled as a linear combination of arousal and ...

Gaussian process dynamical models for multimodal affect recognition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Affective computing systems has a great potential in applications for biofeedback systems and cognitive conductual therapies. Here, by analyzing the physiological behavior of a given subject, we can infer the affective state of an emotional process. ...

[Recognition of Low Arousal Level Electroencephalogram in the Vigilance Based on Wavelet Packet Rhythm and Support Vector Machine].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Poor and monotonous work could easily lead to a decrease of arousal level of the monitoring work personnel. In order to improve the performance of monitoring work, low arousal level needs to be recognized and awakened. We proposed a recognition metho...

Searching arousals: A fuzzy logic approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a computational approach to detect spontaneous, chin tension and limb movement-related arousals by estimating neuronal and muscular activity. Features extraction is carried out by Time Varying Autoregressive Moving Average (TVARMA...

Emotion recognition from sound stimuli based on back-propagation neural networks and electroencephalograms.

The Journal of the Acoustical Society of America
This research aims to explore the feasibility of using back-propagation (BP) neural networks and electroencephalograms (EEGs) to recognize the emotional reactions induced by sound stimuli in the dimensions of pleasure and arousal, as well as compare ...