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Titlebook: Digital Phenotyping and Mobile Sensing; New Developments in Harald Baumeister,Christian Montag Book 20191st edition Springer Nature Switze

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發(fā)表于 2025-3-21 19:51:34 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Digital Phenotyping and Mobile Sensing
副標(biāo)題New Developments in
編輯Harald Baumeister,Christian Montag
視頻videohttp://file.papertrans.cn/280/279595/279595.mp4
概述Describes powerful digital technologies for applications in the study of human behavior.Describes ways to deal with related privacy, ethical and social concerns.With a foreword by Thomas R. Insel, for
叢書(shū)名稱Studies in Neuroscience, Psychology and Behavioral Economics
圖書(shū)封面Titlebook: Digital Phenotyping and Mobile Sensing; New Developments in Harald Baumeister,Christian Montag Book 20191st edition Springer Nature Switze
描述.This book offers a snapshot of cutting-edge applications of mobile sensing for digital phenotyping in the field of Psychoinformatics. The respective chapters, written by authoritative researchers, cover various aspects related to the use of these technologies in health, education, and cognitive science research. They share insights both into established applications of mobile sensing (such as predicting personality or mental and behavioral health on the basis of smartphone usage patterns) and emerging trends. Machine learning and deep learning approaches are discussed, and important considerations regarding privacy risks and ethical issues are assessed. .In addition to essential background information on various technologies and theoretical methods, the book also presents relevant case studies and good scientific practices, thus addressing researchers and professionals alike. To cite Thomas R. Insel, who wrote the foreword to this book: “Patients will only use digital phenotyping if it solves a problem, perhaps a digital smoke alarm that can prevent a crisis. Providers will only use digital phenotyping if it fits seamlessly into their crowded workflow. If we can earn public trust,
出版日期Book 20191st edition
關(guān)鍵詞Smartphone and behavior; Passive sensing in mental health; Mathematical models of users‘ mood; Internet
版次1
doihttps://doi.org/10.1007/978-3-030-31620-4
isbn_softcover978-3-030-31622-8
isbn_ebook978-3-030-31620-4Series ISSN 2196-6605 Series E-ISSN 2196-6613
issn_series 2196-6605
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Ethical Considerations of Digital Phenotyping from the Perspective of a Healthcare Practitionericine and psychiatry, use of digital phenotyping raises several ethical concerns. We use insights derived from a clinical case study to frame these different ethical questions. We discuss how current healthcare practice and privacy policies address these questions and impose requirements for non-hea
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Computerized Facial Emotion Expression Recognitional and valence of emotional expressions. Such ratings are very time-consuming and have limited objectivity due to rater biases. By exploiting improvements in machine learning, the demand for a swifter and more objective method to assess facial emotional expressions was met by a plethora of software.
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Smartphones in Personal Informatics: A Framework for Self-Tracking Research with Mobile Sensingt as being an ideal self-tracking technology that permits both active logging (via self-reports) and passive tracking of information (via phone logs and mobile sensors). In this chapter, we present the results of a literature review of smartphone-based personal informatics studies across three diffe
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發(fā)表于 2025-3-22 13:00:32 | 只看該作者
Digital Brain Biomarkers of Human Cognition and Mooders have several limitations. They are obtrusive, requiring a subject to break from their normal routine. They are episodic and provide sparse snapshots of a patient only at the time of the assessment. They require subjects to perform a task outside of the context of everyday behavior. And lastly, t
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Latest Advances in Computational Speech Analysis for Mobile Sensinga result, any given speech signal contains an abundant array of information about the speaker in terms of both the intended message, i.e., the linguistic content, and insights into particular states and traits relating to the speaker, i.e., the paralinguistic content. In the field of computational s
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