How can large-scale, real-time, and real-world data on people’s behaviors, interactions, and environments improve psychological measurement, or lead to customized psychological interventions? Written expressly for social and behavioral scientists, this cutting-edge handbook describes the key concepts and tools of mobile sensing and explains how to plan and conduct a mobile sensing study. Renowned experts address the whats, whys, and how-tos of collecting "big data" using smartphones and other wearables, and explore which research questions can best be addressed with these tools. Modern statistical methods for analyzing mobile sensing data are described--for example, dynamic structural equation modeling, network modeling, and machine learning, including deep neural networks. The book includes best-practice research examples of applications in clinical psychology, aging, neuroscience, health, emotions, relationships, personality, the workplace, and other areas. Key methodological challenges and ethical/privacy issues are highlighted throughout.

Situations matter. They let people express their personalities and values; provoke motivations, emotions, and behaviors; and are the contexts in which people reason and act. The psychological assessment of situations is a new and rapidly developing area of research, particularly within the fields of personality and social psychology. This volume compiles state-of-the-art knowledge on psychological situations in chapters written by experts in their respective research areas. Bringing together historical reviews, theoretical pieces, methodological descriptions, and empirical applications, this volume is the definitive, go-to source for a psychology of situations.

This book offers a snapshot of cutting-edge applications of digital phenotyping and mobile sensing for studying human behavior and planning innovative e-healthcare interventions. The respective chapters, written by authoritative researchers, cover both theoretical perspectives and good scientific and professional practices related to the use and development of these technologies. They share novel insights into established applications of mobile sensing, such as predicting personality or mental and behavioral health on the basis of smartphone usage patterns, and highlight emerging trends, such as the use of machine learning, big data and deep learning approaches, and the combination of mobile sensing with AI and expert systems. Important issues relating to privacy and ethics are analyzed, together with selected case studies. This thoroughly revised and extended second edition provides researchers and professionals with extensive information on the latest developments in the field of digital phenotyping and mobile sensing. It gives a special emphasis to trends in diagnostics systems and AI applications, suggesting important future directions for research in public health and social sciences.

"The possibilities mobile sensing opens up for the social, behavioral, biomedical, and life sciences appear almost infinite and are bound to become even more comprehensive in the years to come. However, data collection with new information technology also poses new challenges for research and applied fields. Is everything that is possible also legally allowed? What are the personal and societal consequences of the possible deep insights into very private areas of life for research ethics and the relations between the researchers and those being researched? How can data be stored so that anonymity and privacy are preserved? How can quality criteria be formulated for this new and rapidly developing field of research? And how can we ensure that information and predictions derived from mobile sensing are psychometrically accurate and practically useful as we move from scientific proof-of-concept measurements to medical/clinical measurements that aim at supporting and improving the diagnostic process? This handbook answers these questions and based on the conviction that a profound understanding and the sound application of mobile sensing methods require specific knowledge and competencies: scientific background and the key concepts, how to generally plan and conduct a mobile sensing study, different methods of data collection with mobile sensing, both in terms of the technological know-how and the methodological how-to, and possibilities and limitations of mobile sensing and of best-practice examples from different areas of application"--

This book contains the proceedings of the Workshop on Networked Embedded Sensing and Control. This workshop aims at bringing together researchers working on different aspects of networked embedded systems in order to exchange research experiences and to identify the main scientific challenges in this exciting new area.

Proceedings from the latest meeting of the leading AI conference; includes theoretical, experimental, and empirical work. The National Conference on Artificial Intelligence remains the bellwether for research in artificial intelligence. Leading AI researchers and practitioners as well as scientists and engineers in related fields present theoretical, experimental, and empirical results, covering a broad range of topics that include principles of cognition, perception, and action; the design, application, and evaluation of AI algorithms and systems; architectures and frameworks for classes of AI systems; and analyses of tasks and domains in which intelligent systems perform. The Innovative Applications of Artificial Intelligence conference highlights successful applications of AI technology; explores issues, methods, and lessons learned in the development and deployment of AI applications; and promotes an interchange of ideas between basic and applied AI. This volume presents the proceedings of the latest conferences, held in July, 2004.