Emotion and Stress Recognition Related Sensors and Machine Learning Technologies

• Format: eBook
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: activity recognition; affective computing; affective corpus; aging adults; arousal; arousal detection; artificial intelligence; automatic facial emotion recognition; auxiliary loss; behavioral biometrical systems; benchmarking; boredom; center of pressure; class center; classification; cognitive load; computer science; convolutional neural network; convolutional neural networks; correlation statistics; data transformation; dataset; deep convolutional neural network; deep learning; deep neural network; dilated convolutions; driving stress; EEG; elderly caring; electrocardiogram; electrodermal activity; electrodermal activity (EDA); electroencephalography; emotion; emotion classification; emotion elicitation; emotion monitoring; emotion recognition; emotion representation; expert evaluation; face landmark detection; facial detection; facial emotion recognition; facial expression recognition; facial landmarks; feature extraction; feature selection; flight simulation; frustration; fully convolutional DenseNets; GSR; head-mounted display; homography matrix; human-computer interaction; in-ear EEG; information fusion; infrared thermal imaging; intensity of emotion recognition; interest; long short-term memory recurrent neural networks; long-term stress; machine learning; mental stress detection; multimodal sensing; multimodal sensors; musical genres; n/a; normalization; outpatient caring; overload; pain recognition; perceived stress scale; physiological sensing; physiological signal processing; physiological signals; psychophysiology; quantitative analysis; regression; respiration; road traffic; road types; sensor; sensor data analysis; signal analysis; signal processing; similarity measures; skip-connections; smart band; smart insoles; smart shoes; socially assistive robot; stress; stress detection; stress recognition; stress research; stress sensing; subject-dependent emotion recognition; subject-independent emotion recognition; Technology, Engineering, Agriculture, Industrial processes; Technology: general issues; thoracic electrical bioimpedance; time series analysis; transfer learning; underload; unobtrusive sensing; valence detection; Viola-Jones; virtual reality; wearable sensors; weighted loss

This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for c...