摘要

In the present study we compared the performance of three different estimations of local dynamic stability lambda to distinguish between the dynamics of the daily-life walking of elderly fallers and non-fallers. The study re-analyses inertial sensor data of 3-days daily-life activity originally described by Weiss et al. (2013). The data set contains inertial sensor data from 39 older persons who reported less than 2 falls and 31 older persons who reported two or more falls the previous year. 3D-acceleration and 3D-velocity signals from walking epochs of 50 s were used to reconstruct a state space using three different methods. Local dynamic stability was estimated with the algorithms proposed by Rosenstein et al. (1993), Kantz (1994), and Ihlen et al. (2012a). Median lambda s assessed by Ihlen's and Kantz' algorithms discriminated better between elderly fallers and non-fallers (highest AUC=0.75 and 0.73) than Rosenstein's algorithm (highest AUC=0.59). The present results suggest that the ability of lambda to distinguish between fallers and non-fallers is dependent on the parameter setting of the chosen algorithm. Further replication in larger samples of community-dwelling older persons and different patient groups is necessary before including the suggested parameter settings in fall risk assessment and prediction models.

  • 出版日期2016-6-14