Using perceptive computing in multiple sclerosis - the Short Maximum Speed Walk test.

BACKGROUND

We investigated the applicability and feasibility of perceptive computing assisted gait analysis in multiple sclerosis (MS) patients using Microsoft Kinect™. To detect the maximum walking speed and the degree of spatial sway, we established a computerized and observer-independent measure, which we named Short Maximum Speed Walk (SMSW), and compared it to established clinical measures of gait disability in MS, namely the Expanded Disability Status Scale (EDSS) and the Timed 25-Foot Walk (T25FW).

METHODS

Cross-sectional study of 22 MS patients (age mean ± SD 43 ± 9 years, 13 female) and 22 age and gender matched healthy control subjects (HC) (age 37 ± 11 years, 13 female). The disability level of each MS patient was graded using the EDSS (median 3.0, range 0.0-6.0). All subjects then performed the SMSW and the Timed 25-Foot Walk (T25FW). The SMSW comprised five gait parameters, which together assessed average walking speed and gait stability in different dimensions (left/right, up/down and 3D deviation).

RESULTS

SMSW average walking speed was slower in MS patients (1.6 ± 0.3 m/sec) than in HC (1.8 ± 0.4 m/sec) (p = 0.005) and correlated well with EDSS (Spearman's Rho 0.676, p < 0.001). Furthermore, SMSW revealed higher left/right deviation in MS patients compared to HC. SMSW showed high recognition quality and retest-reliability (covariance 0.13 m/sec, ICC 0.965, p < 0.001). There was a significant correlation between SMSW average walking speed and T25FW (Pearson's R = -0.447, p = 0.042).

CONCLUSION

Our data suggest that ambulation tests using Microsoft Kinect™ are feasible, well tolerated and can detect clinical gait disturbances in patients with MS. The retest-reliability was on par with the T25FW.