TITLE:
Case Study on Assessment of Mild Traumatic Brain Injury Using Granular Computing
AUTHORS:
Melaku A. Bogale, Huiying Yu, Thompson Sarkodie-Gyan, Murad Alaqtash, James Moody, Richard Brower
KEYWORDS:
Fuzzy Granular Algorithms; Fuzzy-similarity; Stride-to-stride Variability; Temporal Gait Variables; Dual-task Gait Protocol; Mild Traumatic Brain Injury
JOURNAL NAME:
Engineering,
Vol.4 No.10B,
January
16,
2013
ABSTRACT: Patients
with mild traumatic brain injury complain about having balance and stability
problems despite normal clinical examination. The objective of this study is to
investigate the stride-to-stride gait variability of mTBI subjects while walking
on treadmill under dual-task gait protocols. Fuzzy-granular computing algorithm
is used to objectively quantify the stride-to-stride variability of temporal
gait parameters. The degrees of similarity (DS) of temporal gait parameters in
the dual tasks were determined from the corresponding granulated time-series.
The mTBI group showed relatively smaller degree of similarity for all window
sizes under the cognitive (dual) task walking, showing pronounced
stride-to-stride variability. Different levels of DS among the mTBI subjects
were observed. Individually, both healthy and mTBI group showed different DS
under the two dual-tasks, reflecting the challenging level of the cognitive
tasks while walking. The mean values of the temporal parameters for the mTBI group
were different from the averaged normal reference. On the other hand, the
individual variance analysis shows no significant differences between the
normal and dual task values for some mTBI subjects. The granular approach
however is able to reveal very fine differences and exhibited similar trends
for all mTBI subjects. Different DS values among mTBI group could be indicative
for the different severity level or the undergone rehabilitation process.