Contactless Fall Detection for the Elderly

Book chapter


Nahian, M. J. A., Raju, M. H., Tasnim, Z., Mahmud, M., Ahad, M. and Kaiser, M. S. 2021. Contactless Fall Detection for the Elderly. in: Ahad, M., Mahbub, U. and Rahman, T. (ed.) Contactless Human Activity Analysis Springer, Cham. pp. 203-235
AuthorsNahian, M. J. A., Raju, M. H., Tasnim, Z., Mahmud, M., Ahad, M. and Kaiser, M. S.
EditorsAhad, M., Mahbub, U. and Rahman, T.
Abstract

Early fall detection imposes a challenge for preventing life-threatening conditions to the health in geriatrics. As per the World Health Organization, around that half of total elderly individuals fall every year, which is considered a major cause of death. Fall-down detection and prediction is an active research topic to track seniors who reside at home alone or under treatment in a hospital. With the advancement of pervasive sensing technology and artificial intelligence techniques, automatic and contactless fall detection is now possible via passive monitoring systems. However, such systems’ accuracy is not up to an admissible limit due to the context and ambient conditions. Among the two main categories of fall detection systems, such as wearable sensor-based and contactless sensor-based, security issues of wearable sensor-based detection systems make it unacceptable to researchers. Moreover, wearable sensors are required to be worn by the user for a longer period, making it undesirable by the users. As a result, throughout recent years, ambient and wireless sensor-based systems have been commonly used for fall detection. To define existing approaches for potential research directions, it is important to analyze the elderly fall detection system’s ongoing practices. This book chapter aims to provide a detailed overview of different existing methods/systems of fall detection based on contactless sensors.

Book titleContactless Human Activity Analysis
Page range203-235
Year2021
PublisherSpringer, Cham
Publication dates
Online24 Mar 2021
Publication process dates
Deposited26 Jul 2023
Edition1
SeriesIntelligent Systems Reference Library
ISBN9783030685904
9783030685898
ISSN1868-4394
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-030-68590-4_8
Web address (URL)https://link.springer.com/book/10.1007/978-3-030-68590-4
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