Digital biomechanical biomarkers in the clinical assessment of patients with peripheral neuropathies

The clinical status and treatment response of patients with peripheral neuropathies (PN) rely on subjective and inaccurate clinical scales. Wearable sensors have shown success in evaluating gait and balance in individuals with other neurological disorders. We aimed to explore the ability of biomechanical analysis via wearable technology to monitor disease activity in PN by conducting a single-center, longitudinal study to analyze gait parameters in PN patients and healthy controls using wearable sensors. First, we analyzed the sensor’s ability to detect changes in ataxia and steppage gait severity and found significant differences in spatiotemporal and angular variables. Second, we found correlations between biomechanical features and clinical scales linked to specific gait phenotypes. Finally, we demonstrated that this technology captures clinical changes in gait features over time. Our study provides proof-of-concept that wearable technology effectively detects and grades gait impairment, captures clinically relevant changes, and could enhance gait assessment in routine care and research for PN patients.