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Challenges and Trends in Multimodal Fall Detection for Healthcare

Edited by Hiram Ponce, Edited by Lourdes Martínez-Villaseñor, Edited by Jorge Brieva, Edited by Ernesto Moya-Albor

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normal price: R 4 534.95

Price: R 4 307.95


| book description |

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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Normally shipped | Available from overseas. Usually dispatched in 14 days
Publisher | Springer Nature Switzerland AG
Published date | 29 Jan 2021
Language |
Format | Paperback / softback
Pages | 259
Dimensions | 235 x 155 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-3-0303-8750-1
Readership Age |
BISAC |


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Normally shipped | Usually dispatched in 3 to 6 weeks as supplier is out of stock
Readership Age |
Normal Price | R 4 643.95
Price | R 4 411.95 | on special |



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