Emotion and Stress Recognition Related Sensors and Machine Learning Technologies
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...
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| Other Authors: | , , |
| Format: | eBook |
| Language: | English |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Subjects: | |
| Online Access: | |
| Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
| Summary: | 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 capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective. |
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| Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/ |
| Physical Description: | 1 electronic resource (550 p.) |
| ISBN: | books978-3-0365-1139-9 9783036511399 9783036511382 |