Optimal sensor location and direction to accurately classify people with early-stage multiple sclerosis using gait stability

Background: The local divergence exponent (LDE) has been used to assess gait stability in people with multiple sclerosis (pwMS). Although previous studies have consistently found that stability is lower in pwMS, inconsistent methodologies have been used to assess patients with a broad range of disability levels. Questions: What sensor location and movement direction(s) are better able to classify pwMS at early stages of the disease? Methods: 49 pwMS with EDSS <= 2.5 and 24 healthy controls walked overground for 5 min while 3D acceleration data was obtained from sensors placed at the sternum (STR) and lumbar (LUM) areas. Unidirectional (vertical [VT], mediolateral [ML], and anteroposterior [AP]) and 3-dimensional (3D) LDEs were calculated using STR and LUM data over 150 strides. ROC analyses were performed to assess classification models using single and combined LDEs, with and without velocity per lap (VELLAP) as a covariate. Results: Four models performed equally well by using combinations of VELLAP, LUM3D, LUMVT, LUMML, LUMAP, STRML, and STRAP (AUC = 0.879). The best model using single sensor LDEs included VELLAP, STR3D, STRML, and STRAP (AUC = 0.878), whereas using VELLAP + STRVT (AUC = 0.869) or VELLAP + STR3D (AUC=0.858) performed best using a single LDE. Significance: The LDE offers an alternative to currently insensitive tests of gait impairment in pwMS at early stages, when deterioration is not clinically evident. For clinical purposes, the implementation of this measure can be simplified using a single sensor at the sternum and a single LDE measure, but speed should be considered. Longitudinal studies to determine the predictive power and responsiveness of the LDE to MS progression are still needed.