Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

Joint Authors

Koshmak, Gregory
Linden, Maria
Loutfi, Amy

Source

Journal of Sensors

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2015-12-06

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Civil Engineering

Abstract EN

Emergency situations associated with falls are a serious concern for an aging society.

Yet following the recent development within ICT, a significant number of solutions have been proposed to track body movement and detect falls using various sensor technologies, thereby facilitating fall detection and in some cases prevention.

A number of recent reviews on fall detection methods using ICT technologies have emerged in the literature and an increasingly popular approach considers combining information from several sensor sources to assess falls.

The aim of this paper is to review in detail the subfield of fall detection techniques that explicitly considers the use of multisensor fusion based methods to assess and determine falls.

The paper highlights key differences between the single sensor-based approach and a multifusion one.

The paper also describes and categorizes the various systems used, provides information on the challenges of a multifusion approach, and finally discusses trends for future work.

American Psychological Association (APA)

Koshmak, Gregory& Loutfi, Amy& Linden, Maria. 2015. Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper. Journal of Sensors،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1110571

Modern Language Association (MLA)

Koshmak, Gregory…[et al.]. Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper. Journal of Sensors No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1110571

American Medical Association (AMA)

Koshmak, Gregory& Loutfi, Amy& Linden, Maria. Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper. Journal of Sensors. 2015. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1110571

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1110571