The assessment of standing balance with smartphone technology for the prevention of falls in older adults

Falls;Older adults

Roeing, Kathleen L. ; Sosnoff ; Jacob J.

关键词: Falls;    Older adults;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/98386/ROEING-THESIS-2017.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

One in three adults over the age of 65 will fall in a year, and falls are the leading cause of accidental injury and injury related deaths in this population. Preventative measures to reduce falls include multifactorial fall risk assessments. Balance impairment is routinely used as a measure of fall risk. However, balance assessments require expensive research-grade equipment or clinical expertise. Mobile devices, such as smartphones, provide a potential platform for accessible and inexpensive fall risk assessments. Prior to being implemented in the fall prevention strategies, the concurrent validity, reliability, and usability of such devices needs to be established. The purpose of this thesis was to determine the concurrent validity of a novel smartphone based balance assessment application. Concurrent validity of the novel smartphone balance application was determined by comparing its ability to distinguish the standing balance of young healthy adults (n=15), older adults with low fall risk (as determined by the physiological profile assessment; n=13), and older adults with high fall risk (as determined by the physiological profile assessment; n=17) to the gold standard (force platform). The application was tested under seven different static balance conditions. Repeated measures ANOVAs were used to determine differences between groups on both force platform and smartphone measures. Spearman rank-order correlations were used to evaluate the relationship between force platform and smartphone measures. The Berg Balance Scale, Force platform measures (MVAP and MVRAD), and smartphone measures (Max Accel Y and RMS X) were able to distinguish between low risk and high risk older adults (p≤.05). Spearman rank-order correlations demonstrated 32 moderate correlations (.5≤ρ≤.7) and 9 strong correlations (ρ≥.7) between force platform and smartphone measures. Eight high fall risk older adults were unable to complete all balance conditions, of those five were unable to complete multiple balance conditions. Differences in failure rates were significant between low fall risk older adults and high fall risk older adults. Despite the positive failure rates, no adverse events were recorded. Future research should evaluate additional smartphone accelerometry measures’ ability to distinguish between fallers and non-fallers. It is concluded that smartphone based measures of balance are valid, and safe in older adults.