Gait analysis is essential tool for tracking neurological disorders-Parkinson's disease (PD), stroke, Alzheimer's disease (AD), and multiple sclerosis (MS). Wearable technologies enable continuous, noninvasive gait tracking beyond clinical settings but face challenges in accuracy and adoption. This review investigates wearable gait assessment, identifying patterns and future needs. This rapid umbrella review was conducted, synthesizing systematic reviews and meta-analyses of wearable technologies for gait assessment in PD, stroke, AD, and MS. Following PRISMA guidelines two reviewers screened, extracted data on gait outcomes, and assessed quality using AMSTAR-2. Seventeen reviews (13systematic, 4meta-analyses) encompassing 308 primary studies were included. Most focused-on PD (n = 12), followed by stroke (n = 8), MS (n = 4), and AD (n = 2). Gait was primary outcome, alongside balance, fall risk, and mobility. Wearables (e.g. inertial sensors,) showed good diagnostic accuracy. Real-time biofeedback and exoskeletons improved function. Sensor placement differed greatly, usability was underreported. Lack of standardization, validation, and usability limits clinical adoption. Future efforts must prioritize real-world testing and user-centered design.
Masurkar et al. (Tue,) studied this question.