Body-worn motion sensors detect balance and gait deficits in people with multiple sclerosis who have normal walking speed

Abstract

While balance and gait limitations are hallmarks of multiple sclerosis (MS), standard stopwatch-timed measures practical for use in the clinic are insensitive in minimally affected patients. This prevents early detection and intervention for mobility problems. The study sought to determine if body-worn sensors could detect differences in balance and gait between people with MS with normal walking speeds and healthy controls. Thirty-one MS and twenty-eight age- and sex-matched control subjects were tested using body-worn sensors both during quiet stance and gait (Timed Up and Go test, TUG). Results were compared to stopwatch-timed measures. Stopwatch durations of the TUG and Timed 25 Foot Walk tests were not significantly different between groups. However, during quiet stance with eyes closed, people with MS had significantly greater sway acceleration amplitude than controls (p=0.02). During gait, people with MS had greater trunk angular range of motion in roll (medio-lateral flexion, p=0.017) and yaw (axial rotation, p=0.026) planes. Turning duration through 180° was also longer in MS (p=0.031). Thus, body-worn motion sensors detected mobility differences between MS and healthy controls when traditional timed tests could not. This portable technology provides objective and quantitative mobility data previously not obtainable in the clinic, and may prove a useful outcome measure for early mobility changes in MS.

Conflict of interest statement

Conflicts of interest: There are no conflicts of interest.

Published by Elsevier B.V.

Figures

Fig. 1

The experimental apparatus and protocol. A. A subject performing the quiet standing task, locations of the six body-worn sensors shown. B. Schematic of the walking task divided into gait and postural transition (sit-to-stand, stand-to-sit, turning) phases. C. An example of the motion signal from the walking task showing the horizontal angular velocity of the sternal sensor.

Fig. 2

Timed walking tests did not separate MS from healthy controls using the Timed 25 Foot Walk (T25FW, A), modified Timed Up and Go measured with a stopwatch (mTUG, B), or measured with the body-worn sensors (iTUG, sensors, C). Data points indicate each subject time, horizontal black lines show group means, and white boxes show standard deviations.

Fig.3

Significant differences were found between MS and healthy control subjects during quiet stance, gait and postural transition phases of the instrumented mobility tasks. Cutoffs that maximize sensitivity and specificity of the significant parameters (A, B, D, E) as well as receiver operator characteristic (ROC, C, F) curves are shown. Both means (horizontal black lines) and medians (horizontal grey lines) of the parameters are shown to demonstrate that group effects are driving differences between MS and control and not outliers (A, B, D, E). AUC values are found in Table 1.