The state of knowledge on technologies and their use for fall detection: A scoping review
"Background Globally, populations are aging with increasing life spans. The normal aging process and the resulting disabilities increase fall risks. Falls are an important cause of injury, loss of independence and institutionalization. Technologies have been developed to detect falls and reduce their consequences but their use and impact on quality of life remain debatable. Reviews on fall detection technologies exist but are not extensive. A comprehensive literature review on the state of knowledge of fall detection technologies can inform research, practice, and user adoption. Objectives To examine the extent and the diversity of current technologies for fall detection in older adults. Methods A scoping review design was used to search peer-reviewed literature on technologies to detect falls, published in English, French or Spanish since 2006. Data from the studies were analyzed descriptively. Results The literature search identified 3202 studies of which 118 were included for analysis. Ten types of technologies were identified ranging from wearable (e.g., inertial sensors) to ambient sensors (e.g., vision sensors). Their Technology Readiness Level was low (mean 4.54 SD 1.25; 95% CI [4.31, 4.77] out of a maximum of 9). Outcomes were typically evaluated on technological basis and in controlled environments. Few were evaluated in home settings or care units with older adults. Acceptability, implementation cost and barriers were seldom addressed. Conclusions Further research should focus on increasing Technology Readiness Levels of fall detection technologies by testing them in real-life settings with older adults. © 2017 Elsevier B.V."
Controlled environment ; Attitudes ; Current technology ; Practice ; Falls ; Implementation cost ; Literature reviews ; Older adults ; Scoping review ; Technology readiness levels ; Wearable sensors ; Algorithm ; Assistive technology ; Data mining ; Fuzzy logic ; Hidden Markov model ; Internet ; Journal impact factor ; Knowledge ; Medical information ; Medical technology ; Priority journal ; Qualitative research ; Review ; Support vector machine ; Aged ; Attitude to health ; Falling ; Human ; Quality of life ; Statistics and numerical data ; Accidental Falls ; Aged ; Biomedical Technology ; Health Knowledge ; Humans ; Quality of Life ; Falls ; Older adults ; Scoping review ; Technology ;
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