Challenges and trends in multimodal fall detection for healthcare / Hiram Ponce, Lourdes Martínez-Villaseñor, Jorge Brieva, Ernesto Moya-Albor, editors.
2020
R857.B54
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Details
Title
Challenges and trends in multimodal fall detection for healthcare / Hiram Ponce, Lourdes Martínez-Villaseñor, Jorge Brieva, Ernesto Moya-Albor, editors.
ISBN
9783030387488 (electronic book)
3030387488 (electronic book)
9783030387471
303038747X
3030387488 (electronic book)
9783030387471
303038747X
Publication Details
Cham : Springer, 2020.
Language
English
Description
1 online resource (263 pages).
Call Number
R857.B54
Dewey Decimal Classification
610.285
Summary
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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Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Studies in systems, decision and control ; v. 273.
Available in Other Form
Challenges and Trends in Multimodal Fall Detection for Healthcare
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Online Access
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