Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6950760 | Biomedical Signal Processing and Control | 2018 | 10 Pages |
Abstract
The analysis of selected gait metrics and their correspondence to human gait and balance abilities is presented in this paper. Accelerometric and gyroscopic data have been acquired from 42 older patients for the entire Berg Balance Scale examination along with expert assessments and additional gait segments of a ca. 1â¯min duration evaluated by means of the Tinetti Test. The inertial data is analyzed for gait and step detection and subjected to a detailed gait analysis using four metrics for both legs separately: pitch angle change, average duration of step swing and stance phase, and the average phase duration ratio. The analysis is performed offline. The results are compared to expert assessments using Spearman's rank correlation coefficient with pâ¯<â¯0.001. Three metrics are yielding high correlation up to 0.797 with outcomes delivered by both considered examinations. Moreover, statistically significant differences are obtained for three metrics produced by patients divided into low and medium fall risk groups (Mann-Whitney U test, pâ¯<â¯0.007). The values of the temporal metrics are higher and the angle changes are lower in the medium fall risk group. The proposed features enable the assessment of gait quality and may be of great importance while designing novel tools for quick preliminary fall risk prediction.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Zuzanna Miodonska, Paula Stepien, Pawel Badura, Beata Choroba, Jacek Kawa, JarosÅaw Derejczyk, Ewa Pietka,