AIMC Topic: Arousal

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[Using electroencephalogram for emotion recognition based on filter-bank long short-term memory networks].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Jun 25, 2021
Emotion plays an important role in people's cognition and communication. By analyzing electroencephalogram (EEG) signals to identify internal emotions and feedback emotional information in an active or passive way, affective brain-computer interactio...
Humans Electroencephalography Arousal Neural Networks, Computer Emotions
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A deep learning-based algorithm for detection of cortical arousal during sleep.

Sleep Dec 14, 2020
STUDY OBJECTIVES: The frequency of cortical arousals is an indicator of sleep quality. Additionally, cortical arousals are used to identify hypopneic events. However, it is inconvenient to record electroencephalogram (EEG) data during home sleep test...
Arousal Sleep Polysomnography Algorithms Deep Learning Electroencephalography
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Automatic Detection of Respiratory Effort Related Arousals With Deep Neural Networks From Polysomnographic Recordings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Sleep disorders have become more common due to the modern lifestyle and stress. The most severe case of sleep disorders called apnea is characterized by a complete breaking block, leading to awakening and subsequent sleep disturbances. The automatic ...
Neural Networks, Computer Polysomnography Arousal Machine Learning Sleep
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Deep transfer learning for improving single-EEG arousal detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Datasets in sleep science present challenges for machine learning algorithms due to differences in recording setups across clinics. We investigate two deep transfer learning strategies for overcoming the channel mismatch problem for cases where two d...
Arousal Deep Learning Neural Networks, Computer Machine Learning Electroencephalography
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Statistical algorithms for emotion classification via functional connectivity.

Journal of integrative neuroscience Sep 30, 2019
Pattern recognition algorithms decode emotional brain states by using functional connectivity measures which are extracted from EEG signals as input to the statistical classifiers. An open-access EEG dataset for emotional state analysis is used to cl...
Arousal Signal Processing, Computer-Assisted Neural Pathways Male Support Vector Machine Emotions Electroencephalography Female Adult Brain Humans
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Biosignal-Based Multimodal Emotion Recognition in a Valence-Arousal Affective Framework Applied to Immersive Video Visualization.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Many emotion recognition schemes have been proposed in the state-of-the-art. They generally differ in terms of the emotion elicitation methods, target emotional states to recognize, data sources or modalities, and classification techniques. In this w...
Heart Rate Support Vector Machine Humans Respiration Emotions Arousal Electrocardiography
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Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolution Neural Network.

Studies in health technology and informatics Jan 1, 2019
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 ...
Emotions Arousal Galvanic Skin Response Signal Detection, Psychological Humans Neural Networks, Computer
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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 Aug 1, 2016
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. ...
Normal Distribution Arousal Affect Models, Psychological Humans Support Vector Machine
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[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 Feb 1, 2016
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...
Wavelet Analysis Arousal Electroencephalography Signal Processing, Computer-Assisted Brain Humans Support Vector Machine
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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 Aug 1, 2015
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...
Arousal Neurons Movement Fuzzy Logic
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