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Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Current clinical methods of screening older adults for fall risk have difficulties. Eleven models investigated combined feature effects on classification accuracy, using fold cross-validation.
The models had an average The best performing model including triaxial data, cross-correlations, and traditional measures of gait had Mediolateral signal-based measures—coefficient of variance, cross-correlation with anteroposterior accelerations, and mean acceleration—ranked as the top 3 features. The results suggest accelerometer-based measures captured during walking are potentially useful in screening older women for fall risk.
We are applying algorithms developed in this paper on an OPACH dataset of women with a 1-year prospective falls log and week-long, free-living accelerometer data. Falls are the most common cause of serious injuries in older adults. During , approximately 2. Preventive Services Task Force recommends screening older adults for fall risk and implementing prevention strategies in high-risk adults, such as exercise programs.
There are several methods of screening for fall risk. For example, Lord et al. Existing methods of screening for fall risk typically involve assessments in a clinic or laboratory, and therefore may not reflect fall risk during everyday life activity i. While a variety of devices exist, the use of triaxial accelerometers has several desirable characteristics for screening purposes. Accelerometers are becoming more affordable and available in consumer devices such as smartphones, which are nearly ubiquitous.
