Author(s)

Melaku A. Bogale, Huiying Yu, Thompson Sarkodie-Gyan, Murad Alaqtash, James Moody, Richard Brower

Department of Electrical and Computer Engineering, University of Texas at El Paso, El Paso, Texas, USA.
Department of Medical Education, Texas Tech University Health Sciences Center, El Paso, Texas, USA.
Mentis NeuroRehabilitation, El Paso, Texas, USA.

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.

Fuzzy Granular Algorithms; Fuzzy-similarity; Stride-to-stride Variability; Temporal Gait Variables; Dual-task Gait Protocol; Mild Traumatic Brain Injury

M. Bogale, H. Yu, T. Sarkodie-Gyan, M. Alaqtash, J. Moody and R. Brower, "Case Study on Assessment of Mild Traumatic Brain Injury Using Granular Computing," Engineering, Vol. 4 No. 10B, 2012, pp. 11-15. doi: 10.4236/eng.2012.410B004.