Assessing Disability Level and Fatigue in Multiple Sclerosis With Smart Sock Sensor Technology

Area of Science:

• Biomedical Engineering
• Rehabilitation Science
• Neurology

Background:

• Multiple Sclerosis (MS) significantly impacts mobility and quality of life.
• Objective gait assessment is crucial for monitoring disease progression and treatment efficacy in MS.
• Wearable technology offers potential for continuous and remote patient monitoring.

Purpose of the Study:

• To evaluate the efficacy of smart sock-derived gait metrics in differentiating disability levels in individuals with MS.
• To assess the ability of smart socks to detect fatigue-related gait alterations during prolonged walking in MS.
• To explore the clinical utility of smart sock technology for remote monitoring and personalized rehabilitation in MS.

Main Methods:

• A cross-sectional study involving 32 participants with MS (Patient Determined Disease Steps [PDDS] 0-6).
• Participants completed standardized walking tests (Timed 25-Foot Walk Test, 6-Minute Walk Test, Timed Up-and-Go) wearing smart socks.
• Gait metrics (cadence, speed, temporal phases) and fatigue (Visual Analog Scale for Fatigue) were analyzed.

Main Results:

• Individuals with severe MS disability exhibited significantly slower cadence and speed, with prolonged gait cycle, stance, and double support times compared to those with mild-moderate disability.
• Temporal gait metrics demonstrated high accuracy (ROC-AUCs 0.84-0.87) in discriminating MS disability levels.
• The 6-Minute Walk Test revealed significant increases in gait cycle and double support time, correlating with increased perceived fatigue, indicating motor fatigability.

Conclusions:

• Smart sock technology effectively differentiates MS disability levels using spatiotemporal gait metrics.
• Temporal gait coordination emerged as a primary indicator of impairment in MS.
• Smart socks show promise as scalable tools for remote monitoring and precision rehabilitation in MS care.