Challenges and Trends in Multimodal Fall Detection for Healthcare

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Studies in Systems, Decision and Control 273

ISBN: 303038747X
ISBN 13: 9783030387471
Herausgeber: Hiram Ponce/Lourdes Martínez-Villaseñor/Jorge Brieva et al
Verlag: Springer Verlag GmbH
Umfang: xiii, 259 S.
Erscheinungsdatum: 29.01.2020
Auflage: 1/2020
Produktform: Gebunden/Hardback
Einband: GEB

This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human-machine interaction, among others.

Artikelnummer: 8394139 Kategorie:

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