Gait Characteristics in Spinocerebellar Ataxia Type 3 Assessed Using Wearable Sensors

Research Objectives To investigate a set of gait variability from lower limb wearable sensors that best discriminate between people with healthy or manifest spinocerebellar ataxia (SCA) type 3 and determine how these measures relate to disease severity. Design Case control study. Setting Hospital. Participants 72 patients with genetically confirmed SCA3 (mean age: 44.7 ± 10.5 years) were compared with 38 healthy subjects (mean age: 41.5 ± 15.5 years). Interventions Not applicable. Main Outcome Measures All subjects wore 9 inertial sensors and walked a distance of 22 meters at a natural speed, and only the data of the middle 20 meters were taken for analysis. All patients were scored using the International Cooperative Ataxia Rating Scale (ICARS) and the assessment and rating of ataxia (SARA). Results There were significant differences in gait frequency SD, stride time SD, single support SD, double support SD, toe out angle SD, and toe off angle SD between patients with SCA3 and the normal population (P<0.01). Double support variability (AUC = 0.858) and stride time variability (AUC = 0.849) was the most sensitive and specific gait indicator. Pearson correlation coefficient showed that stride time SD was positively related to SARA-1(Gait, Stance, Sitting, Heel-shin slide) and ICARS-1(Posture and gait disturbances) scores; double support SD was positively related to SARA-1 and ICARS-1 scores (r = 0.486, 0.554, P < 0.001). MLR analysis showed that the regression equation of stride time variability was significant (F = 25.976, p < 0.001). ICARS-1 score (β = 0.686, P < 0.001) was a significant positive predictor of stride time variability while age of onset (β = -0.225, P = 0.021) was a significant negative predictor of stride time variability. These variables accounted for 43% of the variation in stride time variability. Conclusions Wearable sensors can be used to objectively evaluate the degree of impaired gait function in patients with SCA3, in which gait variability characteristics are the most obvious reflection, having certain application value in the treatment of clinical diseases. Author(s) Disclosures The authors declare that they have no conflict of interest.