Stress Detection Based On Multi Modal Data PDF Download

Author: Dr. A Sharada
Publisher: Archers & Elevators Publishing House
ISBN: 8119385489
Category : Antiques & Collectibles
Languages : en
Pages : 90

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Author: Jonathan Aigrain
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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It is now widely accepted that stress plays an important role in modern societies. It impacts the body and the mind at several levels and the association between stress and disease has been observed in several studies. However, there is no consensual definition of stress yet, and therefore there is no consensual way of assessing it either. Thus, although the quality of assessment is a key factor to build robust stress detection solutions, researchers have to choose among a wide variety of assessment strategies. This heterogeneity impacts the validity of comparing solutions among them. In this thesis, we evaluate the impact of several assessment strategies for stress detection. We first review how different fields of research define and assess stress. Then, we describe how we collected stress data along with multiple assessments. We also study the association between these assessments. We present the behavioural and physiological features that we extracted for our experiments. Finally, we present the results we obtained regarding the impact of assessment strategies on 1) data normalization, 2) feature classification performance and 3) on the design of machine learning algorithms. Overall, we argue that one has to take a global and comprehensive approach to design stress detection solutions.

Author: Amit Kumar Singh
Publisher: Elsevier
ISBN: 0443132348
Category : Computers
Languages : en
Pages : 444

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Book Description
Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences. Healthcare experts can make auscultation reports in text format; electrocardiograms can be printed in time series format, x-rays saved as images; volume can be provided through angiography; temporal information by echocardiograms, and 4D information extracted through flow MRI. Another typical source of variability is the existence of data from different time points, such as pre and post treatment, for instance. These large and highly diverse amounts of information need to be organized and mined in an appropriate way so that meaningful information can be extracted. New multimodal data fusion techniques are able to combine salient information into one single source to ensure better diagnostic accuracy and assessment. Data Fusion Techniques and Applications for Smart Healthcare covers cutting-edge research from both academia and industry with a particular emphasis on recent advances in algorithms and applications that involve combining multiple sources of medical information. This book can be used as a reference for practicing engineers, scientists, and researchers. It will also be useful for graduate students and practitioners from government and industry as well as healthcare technology professionals working on state-of-the-art information fusion solutions for healthcare applications. Presents broad coverage of applied case studies using data fusion techniques to mine, organize, and interpret medical data Investigates how data fusion techniques offer a new solution for dealing with massive amounts of medical data coming from diverse sources and multiple formats Focuses on identifying challenges, solutions, and new directions that will be useful for graduate students, researchers, and practitioners from government, academia, industry, and healthcare

Author: Lutz Jäncke
Publisher: Frontiers Media SA
ISBN: 2889711749
Category : Science
Languages : en
Pages : 154

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Author: Guido P. H. Band
Publisher: Frontiers Media SA
ISBN: 2889633527
Category :
Languages : en
Pages : 169

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Author: Masaaki Kurosu
Publisher: Springer Nature
ISBN: 3031604288
Category :
Languages : en
Pages : 278

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Author: Mohamed Tabaa
Publisher: Springer Nature
ISBN: 3031473663
Category : Computers
Languages : en
Pages : 216

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This volume constitutes selected papers presented at the 10th International Conference on Innovation and New Trends in Information Technology, INTIS 2022, held in Casablanca, Morocco, in May 2022, and 11th International Conference on Innovation and New Trends in Information Technology, INTIS 2023, held in Tangier, Morocco, in May 2023. After the thorough peer review process, 4 papers were selected from the 27 submissions received for INTIS 2022, and 11 papers were selected from the 33 submissions received for INTIS 2023. The presented papers cover the mail topics of data-enabled systems/applications: data source layer, network layer, data layer, learning layer, and reporting layers while considering non-functional properties such as data privacy, security, and ethics.

Author: B. Vinoth Kumar
Publisher: Springer Nature
ISBN: 3031205413
Category : Technology & Engineering
Languages : en
Pages : 359

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Book Description
This book addresses and disseminates research and development in the applications of intelligent techniques for computer vision, the field that works on enabling computers to see, identify, and process images in the same way that human vision does, and then providing appropriate output. The book provides contributions which include theory, case studies, and intelligent techniques pertaining to computer vision applications. The book helps readers grasp the essence of the recent advances in this complex field. The audience includes researchers, professionals, practitioners, and students from academia and industry who work in this interdisciplinary field. The authors aim to inspire future research both from theoretical and practical viewpoints to spur further advances in the field.

Author: Shuihua Wang
Publisher: Springer Nature
ISBN: 3031335457
Category : Medical
Languages : en
Pages : 349

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Book Description
This book constitutes the refereed proceedings of the Third EAI International Conference on IoT and Big Data Technologies for Health Care, IotCARE 2022, which took place virtually during December 12-13, 2022. The 23 papers included in this volume were carefully reviewed and selected from 67 submissions. The papers are present newest results in big data technologies for e-health and for e-care. The papers are organized in the following topical sections: big data technologies for e-health; and big data technologies for e-care.

Author: Kyandoghere Kyamakya
Publisher: MDPI
ISBN: 3036511385
Category : Technology & Engineering
Languages : en
Pages : 550

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Book Description
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. This book, emerging from the Special Issue of the Sensors journal on “Emotion and Stress Recognition Related Sensors and Machine Learning Technologies” emerges as a result of the crucial need for massive deployment of intelligent sociotechnical systems. Such technologies are being applied in assistive systems in different domains and parts of the world to address challenges that could not be addressed without the advances made in these technologies.