Emotion and Stress Recognition Related Sensors and Machine Learning Technologies

Format:

Book

Author/Creator:

Kyamakya, Kyandoghere, Editor.

Contributor:

Al-Machot, Fadi, Editor.

Mosa, Ahmad Haj, Editor.

Bouchachia, Hamid, Editor.

Chedjou, Jean Chamberlain, Editor.

Bagula, Antoine, Editor.

Kyamakya, Kyandoghere

Al-Machot, Fadi

Mosa, Ahmad Haj

Bouchachia, Hamid

Chedjou, Jean Chamberlain

Bagula, Antoine

Language:

English

Physical Description:

1 online resource (550 p.)

Place of Publication:

Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021

Language Note:

English

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.