Wearable-based physiological monitoring and brain magnetic resonance imaging metrics in multiple sclerosis: A feasibility study

Abstract

Background Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS). Physiological monitoring may be useful for monitoring the progression of MS and its underlying neurodegenerative processes Objective This cross-sectional study evaluated the feasibility of assessing associations of physiological parameters measured by a wearable sensor with CNS atrophy and lesion burden in individuals with MS. Methods Thirty MS patients (relapsing-remitting [ n = 23], secondary progressive [ n = 5], primary progressive [n = 2]) were monitored using a wrist-worn sensor (Fitbit inspire 3) for up to 30 days, and 29 physiological parameters were obtained. Global and regional brain volumes, T2 lesion volume (T2LV), and C2/3 cervical spinal cord cross-sectional area (C2/3 CSA) were analyzed based on brain MRI. Associations between sensor-derived parameters and neuroimaging measures were assessed using correlation analyses adjusted for age and gender Results The proportion of deep sleep was associated with T2LV (partial spearman's ρ [ρpartial] = −0.46, 95 % confidence interval [−0.74, −0.04]) and C2/3 CSA (ρpartial = 0.59 [0.32, 0.76]). The coefficient of variation of RR intervals during sleep was associated with normalized brain volume (ρpartial = 0.41 [0.00, 0.74]). The minimum (ρpartial = −0.44 [−0.72, −0.04]) and range of heart rate (ρpartial = 0.41 [0.08, 0.68]) during daytime, step counts (ρpartial = 0.64 [0.40, 0.82]), and total metabolic equivalents (ρpartial = 0.54 [0.18, 0.79]) were associated with C2/3 CSA Conclusion The findings suggest the feasibility of using wearable sensors to detect physiological parameters reflective of neuropathology in patients with MS.