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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper
School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden.
Örebro University, School of Science and Technology, Örebro University, Sweden. (AASS)ORCID iD: 0000-0002-3122-693X
School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden.
2016 (English)In: Journal of Sensors, ISSN 1687-725X, E-ISSN 1687-7268, 6931789Article, review/survey (Refereed) Published
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Text
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
Hindawi Publishing Corporation, 2016. 6931789
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-47982DOI: 10.1155/2016/6931789ISI: 000368282900001Scopus ID: 2-s2.0-84953297157OAI: oai:DiVA.org:oru-47982DiVA: diva2:900876
Available from: 2016-02-05 Created: 2016-02-05 Last updated: 2016-02-05Bibliographically approved

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