The book is based on interdisciplinary research on various aspects and dynamics of human multimodal signal exchanges. It discusses realistic application scenarios where human interaction is the focus, in order to identify new methods for data processing and data flow coordination through synchronization, and optimization of new encoding features combining contextually enacted communicative signals, and develop shared digital data repositories and annotation standards for benchmarking the algorithmic feasibility and successive implementation of believable human–computer interaction (HCI) systems. This book is a valuable resource for a. the research community, PhD students, early stage researchers c. schools, hospitals, and rehabilitation and assisted-living centers e. the ICT market, and representatives from multimedia industries
This comprehensive reference work details the latest developments in fluorescence imaging and related biological quantification. It explores the most recent techniques in this imaging technology through the utilization and incorporation of quantification analysis which makes this book unique. It also covers super resolution microscopy with the introduction of 3D imaging and high resolution fluorescence. Many of the chapter authors are world class experts in this medical imaging technology.
Uses the FPT to Solve the Quantification Problem in MRSAn invaluable tool in non-invasive clinical oncology diagnosticsAddressing the critical need in clinical oncology for robust and stable signal processing in magnetic resonance spectroscopy (MRS), Signal Processing in Magnetic Resonance Spectroscopy with Biomedical Applications explores cutting-
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.
This comprehensive volume demonstrates the broad scope of uses for data mining and includes detailed strategies and methodologies for analyzing data from biomedical images, signals, and systems. Written by experts in the field, it presents data mining techniques in the context of various important clinical issues, including diagnosis and grading of depression, identification and classification of arrhythmia and ischemia, and description of classification paradigms for mammograms. The book provides ample information and techniques to benefit researchers, practitioners, and educators of biomedical science and engineering.
Why is there a need today for a new discipline such as neuromanagement? The volume deals with the theme of the applications of neuroscience to organizational contexts evaluating the current impact, the potential for future developments, as well as the critical issues related to neuroscientific paradigms and investigation techniques typical of the neuroscience domain. The first section of the book focuses on the “neuroscientific mindset” for changing, considering, between the other, how leadership can be discovered and empowered by a neuroscientific approach; the neurophysiological components of motivation involved in the pleasure of working and committing for social rewards, positive reinforces, and learning; the practical applications to promote change in the company; how neuromanagement allows us to evaluate and enhance individuals’ executive functions through neuroassessment protocols. The second section suggests well-being and safety as economic leverages, dealing with the issues of promoting trust, managing stress, and applying novel neuroscientific techniques for neuroenhancement. The third section is entitled technology and innovative homo sapiens and describes two main themes: big data application in the company and their possible intersection with the neuroscientific field; moral decision-making processes, able to have an impact on the whole organization and its single members. Or, in other words, this book explores how to discover human beings in organizations through their brains.
The book presents research that contributes to the development of intelligent dialog systems to simplify diverse aspects of everyday life, such as medical diagnosis and entertainment. Covering major thematic areas: machine learning and artificial neural networks; algorithms and models; and social and biometric data for applications in human–computer interfaces, it discusses processing of audio-visual signals for the detection of user-perceived states, the latest scientific discoveries in processing verbal (lexicon, syntax, and pragmatics), auditory (voice, intonation, vocal expressions) and visual signals (gestures, body language, facial expressions), as well as algorithms for detecting communication disorders, remote health-status monitoring, sentiment and affect analysis, social behaviors and engagement. Further, it examines neural and machine learning algorithms for the implementation of advanced telecommunication systems, communication with people with special needs, emotion modulation by computer contents, advanced sensors for tracking changes in real-life and automatic systems, as well as the development of advanced human–computer interfaces. The book does not focus on solving a particular problem, but instead describes the results of research that has positive effects in different fields and applications.
This two-volume set of LNCS 11643 and LNCS 11644 constitutes - in conjunction with the volume LNAI 11645 - the refereed proceedings of the 15th International Conference on Intelligent Computing, ICIC 2019, held in Nanchang, China, in August 2019. The 217 full papers of the three proceedings volumes were carefully reviewed and selected from 609 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology.
Out of the broad arena of sport science and sport psychology, Roland A. Carlstedt presents a comprehensive collection on the neuroscience and associated psychophysiology that underlies and drives sport performance. Featuring sections ranging from the basics and foundations (anatomy and physiology) to the applied (assessment during competition, training, and mental training), Handbook of Sport Neuroscience and Psychophysiology is the first volume to provide students, researchers, practitioners, and coaches the latest knowledge on the brain, mind-body processes, and psychophysiological responding in the context of sport performance.
This book gathers the joint proceedings of the VIII Latin American Conference on Biomedical Engineering (CLAIB 2019) and the XLII National Conference on Biomedical Engineering (CNIB 2019). It reports on the latest findings and technological outcomes in the biomedical engineering field. Topics include: biomedical signal and image processing; biosensors, bioinstrumentation and micro-nanotechnologies; biomaterials and tissue engineering. Advances in biomechanics, biorobotics, neurorehabilitation, medical physics and clinical engineering are also discussed. A special emphasis is given to practice-oriented research and to the implementation of new technologies in clinical settings. The book provides academics and professionals with extensive knowledge on and a timely snapshot of cutting-edge research and developments in the field of biomedical engineering.
