Citation

Ejupi A, Lord SR, Delbaere K. Curr. Opin. Clin. Nutr. Metab. Care 2014; 17(5): 407-411.

Affiliation

aAssistive Healthcare Information Technology Group, Austrian Institute of Technology, Vienna, Austria bVienna University of Technology, Vienna, Austria cNeuroscience Research Australia, University of New South Wales, Sydney, Australia.

Copyright

(Copyright © 2014, Lippincott Williams and Wilkins)

DOI

10.1097/MCO.0000000000000081

PMID

24992225

Abstract

PURPOSE OF REVIEW: Accidental falls are the leading cause of injury-related death and hospitalization in old age, with over one-third of the older adults experiencing at least one fall or more each year. Because of limited healthcare resources, regular objective fall risk assessments are not possible in the community on a large scale. New methods for fall prediction are necessary to identify and monitor those older people at high risk of falling who would benefit from participating in falls prevention programmes. RECENT FINDINGS: Technological advances have enabled less expensive ways to quantify physical fall risk in clinical practice and in the homes of older people. Recently, several studies have demonstrated that sensor-based fall risk assessments of postural sway, functional mobility, stepping and walking can discriminate between fallers and nonfallers. SUMMARY: Recent research has used low-cost, portable and objective measuring instruments to assess fall risk in older people. Future use of these technologies holds promise for assessing fall risk accurately in an unobtrusive manner in clinical and daily life settings.

Language: en