Copyright © 2018 Academy of Geriatric Physical Therapy, APTA. Unauthorized reproduction of this article is prohibited. Journal of GERIATRIC Physical Therapy 1 Systematic Review INTRODUCTION Falls among older people are a serious health issue and can result in hip fractures, traumatic brain injuries, and even fatalities. 1,2 In Australia, the cost of fall-related injuries in older people is more than $200 million per year and is increasing as the population ages. 3 Traditional methods of self-reporting or caregiver reporting of daily activities and fall-related events may be inaccurate due to recall bias, denial, and/or inability for constant monitoring. Remote monitoring using wearable devices is a low-cost alternative and can provide new insights into the complex interactions between active lifestyles, healthy aging, and increased expo- sure to situations in which falls occur. 4 Fall detection using wearable devices has been the focus of substantial recent research and systematic review. 5–10 Body-worn accelerometers detect impacts and changes in orientation associated with falls. 5–8 Accuracy may be improved by using multiple sensors. For example, barom- eters can detect height changes associated with falls, 9 and Android-based smartphones apps have also used gyro- scopes and global position systems to detect falls. 10 These technologies aim to provide rapid detection of falls and, therefore, prevent frail older adults suffering “long lies” due to not being able to get up after a fall. However, detect- ing a fall does not prevent injuries that can result from a fall, including hip fractures and traumatic brain injury. Preventing falls may be facilitated by identifying people at risk of falling and early intervention. Fall risk assess- ments have also been the focus of substantial research and systematic review. 11–16 Existing fall risk tools have gener- ally included clinical assessments of multiple domains, for example, balance, mobility, physiology (strength, vision), psychology (fear of falling), cognition, local environmental risk, and medication use. However, widely accepted tools such as the Timed Up and Go test have low specificity rently the evidence is limited because studies have largely involved simulated laboratory events in young adults. Future studies should focus on validating near-fall detection in larger cohorts and include data from (i) people at high risk of falling, (ii) activities of daily living, (iii) both near falls and actual falls, and (iv) naturally occurring near falls. Key Words: accelerometer, fall, near, old, wearable (J Geriatr Phys Ther 2018;00:1-9.) ABSTRACT Background and Purpose: Falls among older people are a seri- ous health issue. Remote detection of near falls may provide a new way to identify older people at high risk of falling. This could enable exercise and fall prevention programs to target the types of near falls experienced and the situations that cause near falls before fall-related injuries occur. The purpose of this systematic review was to summarize and critically examine the evidence regarding the detection of near falls (slips, trips, stumbles, missteps, incorrect weight transfer, or temporary loss of balance) using wearable devices. Methods: CINAHL, EMBASE, MEDLINE, Compendex, and Inspec were searched to obtain studies that used a wearable device to detect near falls in young and older people with or without a chronic disease and were published in English. Results: Nine studies met the final inclusion criteria. Wear- able sensors used included accelerometers, gyroscopes, and insole force inducers. The waist was the most common loca- tion to place a single device. Both high sensitivity ( ≥85.7%) and specificity ( ≥90.0%) were reported for near-fall detec- tion during various clinical simulations and improved when multiple devices were worn. Several methodological issues that increased the risk of bias were revealed. Most studies analyzed a single or few near-fall types by younger adults in controlled laboratory environments and did not attempt to distinguish naturally occurring near falls from actual falls or other activities of daily living in older people. Conclusions: The use of a single lightweight sensor to distin- guish between different types of near falls, actual falls, and activities of daily living is a promising low-cost technology and clinical tool for long-term continuous monitoring of older people and clinical populations at risk of falls. However, cur- Detection of Near Falls Using Wearable Devices: A Systematic Review Ivan Pang, BE 1 ; Yoshiro Okubo, PhD 2 ; Daina Sturnieks, PhD 2,3 ; Stephen R. Lord, DSc 2,3 ; Matthew A. Brodie, PhD 1,2 1 Graduate School of Biomedical Engineering, University of New South Wales, Randwick, Sydney, Australia. 2 Neuroscience Research Australia, University of New South Wales, Randwick, Sydney, Australia. 3 Faculty of Medicine, University of New South Wales, Randwick, Sydney, Australia. The authors declare no conflicts of interest. Systematic review registration: CRD42016047693 Kevin Chui was the Decision Editor Address correspondence to: Matthew A. Brodie, PhD, Neuroscience Research Australia, University of New South Wales, Barker St, Randwick, Sydney, NSW 2031, Australia (matthew.brodie@neura.edu.au). Copyright © 2018 Academy of Geriatric Physical Therapy, APTA DOI: 10.1519/JPT.0000000000000181