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. 2022 Sep 7;22(18):6752.
doi: 10.3390/s22186752.

A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults

Manting Chen  1 , Hailiang Wang  2 , Lisha Yu  3 , Eric Hiu Kwong Yeung  4 , Jiajia Luo  1 , Kwok-Leung Tsui  5 , Yang Zhao  1
Affiliations

A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults

Manting Chen et al. Sensors (Basel). .

Abstract

Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling.

Keywords: community-dwelling older adults; fall risk assessment; functional test; sensor technology.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
The number of articles on wearable sensor-based technologies for fall risk assessment in older adults published between 2011 and 2021, retrieved from Google Scholar.
Figure 2
Figure 2
The number of relevant articles retrieved from PubMed, Scopus, and Web of Science between November 2017 and June 2022.
Figure 3
Figure 3
Flowchart of article selection process for the systematic review.
Figure 4
Figure 4
Summary of sensor information available in the reviewed studies.
Figure 5
Figure 5
Association between sensor location and type.
Figure 6
Figure 6
Recommended and not recommended sensor locations for data collection. (a) Recommended locations; (b) Not recommended locations.
See this image and copyright information in PMC

References

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