Challenges and Trends in Multimodal Fall Detection for Healthcare
Hiram Ponce (u. a.)
ISBN 10: 303038750X ISBN 13: 9783030387501
Editorial: Springer, 2021
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Descripción
Descripción:
Challenges and Trends in Multimodal Fall Detection for Healthcare | Hiram Ponce (u. a.) | Taschenbuch | Studies in Systems, Decision and Control | xiii | Englisch | 2021 | Springer | EAN 9783030387501 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de ref. del artículo 119520908
Sinopsis:
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.
De la contraportada:
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.
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Detalles bibliográficos
Título: Challenges and Trends in Multimodal Fall ...
Editorial: Springer
Año de publicación: 2021
Encuadernación: Taschenbuch
Condición: Neu