Introduction To Eeg And Speech Based Emotion Recognition
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Introduction to EEG- and Speech-Based Emotion Recognition by Priyanka A. Abhang,Bharti W. Gawali,Suresh C. Mehrotra Pdf
Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using electroencephalograms (EEGs) to detect and recognize different emotions. By incorporating these methods in brain-computer interface (BCI), we can achieve more natural, efficient communication between humans and computers. This book discusses how emotional states can be recognized in EEG images, and how this is useful for BCI applications. EEG and speech processing methods are explored, as are the technological basics of how to operate and record EEGs. Finally, the authors include information on EEG-based emotion recognition, classification, and a proposed EEG/speech fusion method for how to most accurately detect emotional states in EEG recordings. Provides detailed insight on the science of emotion and the brain signals underlying this phenomenon Examines emotions as a multimodal entity, utilizing a bimodal emotion recognition system of EEG and speech data Details the implementation of techniques used for acquiring as well as analyzing EEG and speech signals for emotion recognition
How will artificial intelligence (AI), reshape work, commerce, relationships, and reality? As AI shatters barriers and ascends to CEO positions, rewriting the rules of our world, it renders millions who were previously considered impervious, vulnerable to its effects. When a tranquil Canadian evening takes a sinister turn, an elderly couple becomes ensnared in a cruel deception that exposes the unsettling complexities of AI. Surpassing the scope of science fiction and our brain’s ability to comprehend it, AI is on a path to alter society's foundation, adeptly replacing jobs and instigating a major shift in social roles—ushering a new economic era. Yet, few are prepared to adapt. "The Wolf Is at the Door" invites you on a compelling journey, unveiling this dramatic transformation and providing crucial insights for entrepreneurs and workers alike. Unraveling the boundless possibilities and problems borne by the digital frontier, this book breaks down the 10 most pressing threats we face and 10 vital rules to thrive in an AI-driven world. As you explore the latest jaw-dropping developments, you will travel from the bustling center of Manhattan to the tranquil farmlands of Australia, bearing witness to enduring echoes of the past—from the Great Depression to the Industrial Revolution—on a quest to answer the defining questions of our generation. However, caution is necessary. When you meet the wolf, will he morph into an accomplice of immeasurable benefits, or surface as an adversary taking over your job or venture? It's up to you to decide.
ICDSMLA 2019 by Amit Kumar,Marcin Paprzycki,Vinit Kumar Gunjan Pdf
This book gathers selected high-impact articles from the 1st International Conference on Data Science, Machine Learning & Applications 2019. It highlights the latest developments in the areas of Artificial Intelligence, Machine Learning, Soft Computing, Human–Computer Interaction and various data science & machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.
Emotion and Stress Recognition Related Sensors and Machine Learning Technologies by Kyandoghere Kyamakya,Fadi Al-Machot,Ahmad Haj Mosa,Hamid Bouchachia,Jean Chamberlain Chedjou,Antoine Bagula Pdf
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.
Proceeding of the 3rd International Conference on Electronics, Biomedical Engineering, and Health Informatics by Triwiyanto Triwiyanto,Achmad Rizal,Wahyu Caesarendra Pdf
This book presents high-quality peer-reviewed papers from the International Conference on Electronics, Biomedical Engineering, and Health Informatics (ICEBEHI) 2022 held at Surabaya, Indonesia, virtually. The contents are broadly divided into three parts: (a) Electronics, (b) Biomedical Engineering, and (c) Health Informatics. The major focus is on emerging technologies and their applications in the domain of biomedical engineering. It includes papers based on original theoretical, practical, and experimental simulations, development, applications, measurements, and testing. Featuring the latest advances in the field of biomedical engineering applications, this book serves as a definitive reference resource for researchers, professors, and practitioners interested in exploring advanced techniques in the fields of electronics, biomedical engineering, and health informatics. The applications and solutions discussed here provide excellent reference material for future product development.
Neuropsychogical Trends 25 - April 2019 by AA. VV. Pdf
Richard H. Morley - Paul B. Jantz - Reiko Graham, The Salience Network structures as a mediator of violence and perceptions of hostility - Sara Invitto - Carola Capone - Graziano Gigante - Giulia Piraino - Bianca Sisinni, The effect of acoustic feedback in an auditory Posner paradigm: delay effect and bias in ERP - Seyedeh Maryam Moshirian Farahi - Mohammad Javad Asghari Ebrahimabad - Ali Gorji - Imanollah Bigdeli - Seyed Mohammad Mahdi Moshirian Farahi, Cortical brain activities related to neuroticism and extraversion in adolescence - Laura Angioletti - Michela Balconi, What is the role of metacognition in Parkinson’s Disease patients with Pathological Gambling? - Ymie J. Van Der Zee - Peter L.J. Stiers - Lieven Lagae - Johan J.M. Pel - Heleen M. Evenhuis, Chronological age versus developmental age in evaluating patients’ performances on motion perception tests - Irene Venturella - Davide Crivelli - Marina Fossati - Francesca Fiorillo - Michela Balconi, Fronto-parietal network in response to pleasant and unpleasant somatic stimuli in DoC patients: a pilot study
Encyclopedia of Computer Graphics and Games by Newton Lee Pdf
Encyclopedia of Computer Graphics and Games (ECGG) is a unique reference resource tailored to meet the needs of research and applications for industry professionals and academic communities worldwide. The ECGG covers the history, technologies, and trends of computer graphics and games. Editor Newton Lee, Institute for Education, Research, and Scholarships, Los Angeles, CA, USA Academic Co-Chairs Shlomo Dubnov, Department of Music and Computer Science and Engineering, University of California San Diego, San Diego, CA, USA Patrick C. K. Hung, University of Ontario Institute of Technology, Oshawa, ON, Canada Jaci Lee Lederman, Vincennes University, Vincennes, IN, USA Industry Co-Chairs Shuichi Kurabayashi, Cygames, Inc. & Keio University, Kanagawa, Japan Xiaomao Wu, Gritworld GmbH, Frankfurt am Main, Hessen, Germany Editorial Board Members Leigh Achterbosch, School of Science, Engineering, IT and Physical Sciences, Federation University Australia Mt Helen, Ballarat, VIC, Australia Ramazan S. Aygun, Department of Computer Science, Kennesaw State University, Marietta, GA, USA Barbaros Bostan, BUG Game Lab, Bahçeşehir University (BAU), Istanbul, Turkey Anthony L. Brooks, Aalborg University, Aalborg, Denmark Guven Catak, BUG Game Lab, Bahçeşehir University (BAU), Istanbul, Turkey Alvin Kok Chuen Chan, Cambridge Corporate University, Lucerne, Switzerland Anirban Chowdhury, Department of User Experience and Interaction Design, School of Design (SoD), University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India Saverio Debernardis, Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Bari, Italy Abdennour El Rhalibi, Liverpool John Moores University, Liverpool, UK Stefano Ferretti, Department of Computer Science and Engineering, University of Bologna, Bologna, Italy Han Hu, School of Information and Electronics, Beijing Institute of Technology, Beijing, China Ms. Susan Johnston, Select Services Films Inc., Los Angeles, CA, USA Chris Joslin, Carleton University, Ottawa, Canada Sicilia Ferreira Judice, Department of Computer Science, University of Calgary, Calgary, Canada Hoshang Kolivand, Department Computer Science, Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, UK Dario Maggiorini, Department of Computer Science, University of Milan, Milan, Italy Tim McGraw, Purdue University, West Lafayette, IN, USA George Papagiannakis, ORamaVR S.A., Heraklion, Greece; FORTH-ICS, Heraklion Greece University of Crete, Heraklion, Greece Florian Richoux, Nantes Atlantic Computer Science Laboratory (LINA), Université de Nantes, Nantes, France Andrea Sanna, Dipartimento di Automatica e Informatica, Politecnico di Torino, Turin, Italy Yann Savoye, Institut fur Informatik, Innsbruck University, Innsbruck, Austria Sercan Şengün, Wonsook Kim School of Art, Illinois State University, Normal, IL, USA Ruck Thawonmas, Ritsumeikan University, Shiga, Japan Vinesh Thiruchelvam, Asia Pacific University of Technology & Innovation, Kuala Lumpur, Malaysia Rojin Vishkaie, Amazon, Seattle, WA, USA Duncan A. H. Williams, Digital Creativity Labs, Department of Computer Science, University of York, York, UK Sai-Keung Wong, National Chiao Tung University, Hsinchu, Taiwan Editorial Board Intern Sam Romershausen, Vincennes University, Vincennes, IN, USA
Applications of Artificial Intelligence in Healthcare and Biomedicine by Abdulhamit Subasi Pdf
??Applications of Artificial Intelligence in Healthcare and Biomedicine provides ?updated knowledge on the applications of artificial intelligence in medical image analysis. The book starts with an introduction to Artificial Intelligence techniques for Healthcare and Biomedicine. In 16 chapters it presents artificial applications in Electrocardiogram (ECG), Electroencephalogram (EEG) and Electromyography (EMG), signal analysis, Computed Tomography (CT), Magnetic Resonance Imaging (MR) and Ultrasound image analysis. It equips researchers with tools for early breast cancer detection from mammograms using artificial intelligence (AI), AI models to detect lung cancer using histopathological images and a deep learning-based approach to get a proper and faster diagnosis of the Optical Coherence Tomography (OCT) images. It also presents present 3D medical image analysis using 3D Convolutional Neural Networks (CNNs). Applications of Artificial Intelligence in Healthcare and Biomedicine closes with a chapter on AI-based approach to forecast diabetes patients' hospital re-admissions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about the applications of Artificial Intelligence and its impact in medical/biomedical image analysis. Provides knowledge on Artificial Intelligence algorithms for clinical data analysis Gives insights into both AI applications in biomedical signal analysis, biomedical image analysis, and applications in healthcare, including drug discovery Equips researchers with tools for early breast cancer detection
Law and Artificial Intelligence by Bart Custers,Eduard Fosch-Villaronga Pdf
This book provides an in-depth overview of what is currently happening in the field of Law and Artificial Intelligence (AI). From deep fakes and disinformation to killer robots, surgical robots, and AI lawmaking, the many and varied contributors to this volume discuss how AI could and should be regulated in the areas of public law, including constitutional law, human rights law, criminal law, and tax law, as well as areas of private law, including liability law, competition law, and consumer law. Aimed at an audience without a background in technology, this book covers how AI changes these areas of law as well as legal practice itself. This scholarship should prove of value to academics in several disciplines (e.g., law, ethics, sociology, politics, and public administration) and those who may find themselves confronted with AI in the course of their work, particularly people working within the legal domain (e.g., lawyers, judges, law enforcement officers, public prosecutors, lawmakers, and policy advisors). Bart Custers is Professor of Law and Data Science at eLaw - Center for Law and Digital Technologies at Leiden University in the Netherlands. Eduard Fosch-Villaronga is Assistant Professor at eLaw - Center for Law and Digital Technologies at Leiden University in the Netherlands.
Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning by Saeed Mian Qaisar,Humaira Nisar,Abdulhamit Subasi Pdf
This book presents the modern technological advancements and revolutions in the biomedical sector. Progress in the contemporary sensing, Internet of Things (IoT) and machine learning algorithms and architectures have introduced new approaches in the mobile healthcare. A continuous observation of patients with critical health situation is required. It allows monitoring of their health status during daily life activities such as during sports, walking and sleeping. It is realizable by intelligently hybridizing the modern IoT framework, wireless biomedical implants and cloud computing. Such solutions are currently under development and in testing phases by healthcare and governmental institutions, research laboratories and biomedical companies. The biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG), Electromyography (EMG), phonocardiogram (PCG), Chronic Obstructive Pulmonary (COP), Electrooculography (EoG), photoplethysmography (PPG), and image modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and computerized tomography (CT) are non-invasively acquired, measured, and processed via the biomedical sensors and gadgets. These signals and images represent the activities and conditions of human cardiovascular, neural, vision and cerebral systems. Multi-channel sensing of these signals and images with an appropriate granularity is required for an effective monitoring and diagnosis. It renders a big volume of data and its analysis is not feasible manually. Therefore, automated healthcare systems are in the process of evolution. These systems are mainly based on biomedical signal and image acquisition and sensing, preconditioning, features extraction and classification stages. The contemporary biomedical signal sensing, preconditioning, features extraction and intelligent machine and deep learning-based classification algorithms are described. Each chapter starts with the importance, problem statement and motivation. A self-sufficient description is provided. Therefore, each chapter can be read independently. To the best of the editors’ knowledge, this book is a comprehensive compilation on advances in non-invasive biomedical signal sensing and processing with machine and deep learning. We believe that theories, algorithms, realizations, applications, approaches, and challenges, which are presented in this book will have their impact and contribution in the design and development of modern and effective healthcare systems.
Computational Techniques in Neuroscience by Kamal Malik,Harsh Sadawarti,Moolchand Sharma,Umesh Gupta,Prayag Tiwari Pdf
The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using artificial intelligence, deep learning, and other machine learning techniques to fine-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
Emotion and Attention Recognition Based on Biological Signals and Images by Seyyed Abed Hosseini Pdf
Emotion, stress, and attention recognition are the most important aspects in neuropsychology, cognitive science, neuroscience, and engineering. Biological signals and images processing such as galvanic skin response (GSR), electrocardiography (ECG), heart rate variability (HRV), electromyography (EMG), electroencephalography (EEG), event-related potentials (ERP), eye tracking, functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) have a great help in understanding the mentioned cognitive processes. Emotion, stress, and attention recognition systems based on different soft computing approaches have many engineering and medical applications. The book Emotion and Attention Recognition Based on Biological Signals and Images attempts to introduce the different soft computing approaches and technologies for recognition of emotion, stress, and attention, from a historical development, focusing particularly on the recent development of the field and its specialization within neuropsychology, cognitive science, neuroscience, and engineering. The basic idea is to present a common framework for the neuroscientists from diverse backgrounds in the cognitive neuroscience to illustrate their theoretical and applied research findings in emotion, stress, and attention.
The Routledge Companion to Marketing Research by Len Tiu Wright,Luiz Moutinho,Merlin Stone,Richard P. Bagozzi Pdf
This single-volume reference provides an alternative to traditional marketing research methods handbooks, focusing entirely on the new and innovative methods and technologies that are transforming marketing research and practice. Including original contributions and case studies from leading global specialists, this handbook covers many pioneering methods, such as: Methods for the analysis of user- and customer-generated data, including opinion mining and sentiment analysis Big data Neuroscientific techniques and physiological measures Voice prints Human–computer interaction Emerging approaches such as shadowing, netnographies and ethnographies Transcending the old divisions between qualitative and quantitative research methods, this book is an essential tool for market researchers in academia and practice.
IoT-Based Data Analytics for the Healthcare Industry by Sanjay Kumar Singh,Ravi Shankar Singh,Anil Kumar Pandey,Sandeep S Udmale,Ankit Chaudhary Pdf
IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization. The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand. Provides state-of-art methods and current trends in data analytics for the healthcare industry Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques Discusses several potential AI techniques developed using IoT for the healthcare industry Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages
