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"--

Digital Health: Mobile and Wearable Devices for Participatory Health Applications is a key reference for engineering and clinical professionals considering the development or implementation of mobile and wearable solutions in the healthcare domain. The book presents a comprehensive overview of devices and appropriateness for the respective applications. It also explores the ethical, privacy, and cybersecurity aspects inherent in networked and mobile technologies. It offers expert perspectives on various approaches to the implementation and integration of these devices and applications across all areas of healthcare. The book is designed with a multidisciplinary audience in mind; from software developers and biomedical engineers who are designing these devices to clinical professionals working with patients and engineers on device testing, human factors design, and user engagement/compliance. - Presents an overview of important aspects of digital health, from patient privacy and data security to the development and implementation of networks, systems, and devices - Provides a toolbox for stakeholders involved in the decision-making regarding the design, development, and implementation of mHealth solutions - Offers case studies, key references, and insights from a wide range of global experts

Recently, digital interventions have proliferated and show promising results in preventing and treating common mental health disorders, such as depression, in different settings (e.g., workplaces). Digital interventions may have advantages over face-to-face interventions (e.g., more accessible; easily customisable; real-time monitoring). However, despite efforts made by healthcare systems worldwide (e.g., apps on prescription in Germany), actual adoption is still rather low in many countries. It is essential to understand innovation acceptance in order to tailor digital interventions and to measure user technology acceptance. In this way, determinants can be identified to derive strategies to promote acceptance. Technology acceptance has been studied extensively, resulting in the development of various theoretical models (e.g., Technology Acceptance Model-TAM; Unified Theory of Acceptance and Use of Technology-UTAUT, UTAUT2). Besides several methodological strengths, technology acceptance models also have various limitations, which makes it difficult to investigate causality or to generalize findings across different contexts, populations, and cultures.

"Teleneurology" refers to the use of telecommunications techniques such as the telephone, Internet, email, and videoconferencing to improve the delivery of neurology services. Containing 15 contributions from international clinicians, this volume provides an introduction to telemedicine as it is practiced in neurology today. It is divided into three sections: techniques, applications, and practical issues. Technical information has been kept to a minimum, as the emphasis is on the utility of each technique, rather than the technology itself. The editors are affiliated with the Center for Online Health at the U. of Queensland in Australia. Annotation :2005 Book News, Inc., Portland, OR (booknews.com).