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.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Systems Reference Library |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 203-235 |
| Number of pages | 33 |
| DOIs | |
| State | Published - 2021 |
| Externally published | Yes |
Publication series
| Name | Intelligent Systems Reference Library |
|---|---|
| Volume | 200 |
| ISSN (Print) | 1868-4394 |
| ISSN (Electronic) | 1868-4408 |
Bibliographical note
Publisher Copyright:© 2021, Springer Nature Switzerland AG.
ASJC Scopus subject areas
- General Computer Science
- Information Systems and Management
- Library and Information Sciences
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