13 research outputs found
Maximum walking speed in multiple sclerosis assessed with visual perceptive computing
<div><p>Background</p><p>Gait is often impaired in people with multiple sclerosis (PwMS), but detailed assessment of gait impairment in research and care remains challenging. In a previous pilot study we reported the feasibility of visual perceptive computing (VPC) for gait assessment in PwMS using the Short Maximum Speed Walk (SMSW), which assesses gait on recording distances confined to less than 4 meters.</p><p>Objective</p><p>To investigate the equivalence of SMSW to rater-based timed 25ft. walk (T25FW) in a large cohort of PwMS, and to investigate the association of SMSW-derived gait parameters with clinical disability, as well as subjective and objective gait impairment, in order to validate the SMSW as a quick and objective measure of clinical relevance possibly superior to T25FW.</p><p>Methods</p><p>95 PwMS and 60 healthy controls (HC) performed the SMSW using a VPC system with Microsoft Kinect. All participants received two immediate retests to establish test-retest-reliability. Both PwMS and HC performed the T25FW. PwMS were rated according to the Expanded Disability Status Scale (EDSS) and answered the 12-item Multiple Sclerosis Walking Scale (MSWS-12) as a measure of self-perceived walking impairment.</p><p>Results</p><p>PwMS showed reduced average speed (p<0.001) and higher mediolateral deviation (p = 0.002) during SMSW than HC. Average speed was the most reliable SMSW parameter in PwMS and HC (intra-class correlation coefficient (ICC) in PwMS = 0.985, and in HC = 0.977). Average speed declined with age in PwMS and HC (r in PwMS = -0.648, and in HC = -0.452, both p<0.001). Correlation of SMSW average speed and T25FW speed was high in both groups (r in PwMS = 0.783, and in HC = 0.747, both p<0.001) and mean difference (0.0013 m/s) between methods was below smallest detectable change. Average speed correlated well with both clinical disability based on EDSS (r = -0.586, p<0.001) and self-perceived walking impairment based on MSWS-12 (r = -0.546, p<0.001).</p><p>Conclusion</p><p>VPC-assessed walking parameters during SMSW can reliably detect gait disturbance in PwMS over very short distance. Specifically, maximum gait speed can be obtained with high accuracy in this simple test set-up. Cross-sectional associations with disability and self-perceived walking impairment support clinical relevance. Given its objectivity in a simple test set-up, SMSW is superior to T25FW.</p></div
Demographic confounders in HC (A) and PwMS (B).
<p>Demographic confounders in HC (A) and PwMS (B).</p
Bland-Altman plot of the differences between SMSW average speed and T25FW speed.
<p>Mean difference (solid line) and limits of confidence (dashed lines) refer to the whole dataset. For better interpretation, HC are rendered as open circles and PwMS as filled circles. In two HC and two PwMS, the difference between both maximum speeds was outside the limits of agreement. All four showed an overestimation of T25FW versus SMSW average speed but did not have any other specific feature in common.</p
Univariate regression of maximum walking speed assessed with SMSW (average speed (A)) or T25FW (B) and with age as factor in HC (open circles, dashed lines) and PwMS (filled circles, continuous lines).
<p>Regression lines are given along with their 95% confidence intervals.</p
Test-retest-reliability and smallest real difference.
<p>Test-retest-reliability and smallest real difference.</p
Demographics, clinical and MRI findings and EBV parameters at baseline of patients and healthy controls analyzed in this study.
<p>Demographics, clinical and MRI findings and EBV parameters at baseline of patients and healthy controls analyzed in this study.</p