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Challenges and Issues in Multi-Sensor FusionApproach for Fall Detection: Review Paper
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-0712-6015
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1940-1747
2016 (English)In: Journal of Sensors, ISSN 1687-725X, E-ISSN 1687-7268, 6931789Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
2016. 6931789
Keyword [en]
Aging societies; Body movements; Emergency situation; Fall detection; Multifusion; Review papers; Sensor technologies; Single sensor
National Category
Health Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:mdh:diva-27955DOI: 10.1155/2016/6931789ISI: 000368282900001Scopus ID: 2-s2.0-84953297157OAI: oai:DiVA.org:mdh-27955DiVA: diva2:811050
Available from: 2015-05-10 Created: 2015-05-10 Last updated: 2016-10-31Bibliographically approved

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Publisher's full textScopushttp://www.hindawi.com/journals/js/2016/6931789/

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