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. 2014 Apr 22;14(4):7181-208.
doi: 10.3390/s140407181.

Smartphone-based solutions for fall detection and prevention: challenges and open issues

Mohammad Ashfak Habib  1 , Mas S Mohktar  2 , Shahrul Bahyah Kamaruzzaman  3 , Kheng Seang Lim  4 , Tan Maw Pin  5 , Fatimah Ibrahim  6
Affiliations

Smartphone-based solutions for fall detection and prevention: challenges and open issues

Mohammad Ashfak Habib et al. Sensors (Basel). .

Abstract

This paper presents a state-of-the-art survey of smartphone (SP)-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention. Required hardware for both fall detection and prevention are also available in SPs. Consequently, researchers' interest in finding SP-based solutions has increased dramatically over recent years. To the best of our knowledge, there has been no published review on SP-based fall detection and prevention. Thus in this paper, we present the taxonomy for SP-based fall detection and prevention solutions and systematic comparisons of existing studies. We have also identified three challenges and three open issues for future research, after reviewing the existing articles. Our time series analysis demonstrates a trend towards the integration of external sensing units with SPs for improvement in usability of the systems.

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Figures

Figure 1.
Figure 1.
Common basic architecture of fall detection and fall prevention systems.
Figure 2.
Figure 2.
Taxonomy of smartphone-based systems based on sensing mechanism and sensor placement.
Figure 3.
Figure 3.
Taxonomy of smartphone based fall detection and prevention algorithms.
Figure 4.
Figure 4.
Taxonomy of communication patterns in smartphone-based fall detection and prevention systems.
Figure 5.
Figure 5.
Estimation of the number of SP based fall detection and prevention studies.
See this image and copyright information in PMC

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