@article{ref1,
title="Improved prediction of falls in community-dwelling older adults through phase-dependent entropy of daily-life walking",
journal="Frontiers in aging neuroscience",
year="2018",
author="Ihlen, Espen A. F. and van Schooten, Kimberley S. and Bruijn, Sjoerd M. and van Dieen, Jaap H. and Vereijken, Beatrix and Helbostad, Jorunn L. and Pijnappels, Mirjam",
volume="10",
number="",
pages="e44-e44",
abstract="Age and age-related diseases have been suggested to decrease entropy of human gait kinematics, which is thought to make older adults more susceptible to falls. In this study we introduce a new entropy measure, called phase-dependent generalized multiscale entropy (PGME), and test whether this measure improves fall-risk prediction in community-dwelling older adults. PGME can assess phase-dependent changes in the stability of gait dynamics that result from kinematic changes in events such as heel strike and toe-off. PGME was assessed for trunk acceleration of 30 s walking epochs in a re-analysis of 1 week of daily-life activity data from the FARAO study, originally described by van Schooten et al. (2016). The re-analyzed data set contained inertial sensor data from 52 single- and 46 multiple-time prospective fallers in a 6 months follow-up period, and an equal number of non-falling controls matched by age, weight, height, gender, and the use of walking aids. The predictive ability of PGME for falls was assessed using a partial least squares regression. PGME had a superior predictive ability of falls among single-time prospective fallers when compared to the other gait features. The single-time fallers had a higher PGME (<i>p</i>< 0.0001) of their trunk acceleration at 60% of their step cycle when compared with non-fallers. No significant differences were found between PGME of multiple-time fallers and non-fallers, but PGME was found to improve the prediction model of multiple-time fallers when combined with other gait features. These findings suggest that taking into account phase-dependent changes in the stability of the gait dynamics has additional value for predicting falls in older people, especially for single-time prospective fallers.<p /> <p>Language: en</p>",
language="en",
issn="1663-4365",
doi="10.3389/fnagi.2018.00044",
url="http://dx.doi.org/10.3389/fnagi.2018.00044"
}