Abstract
Purpose: Wearable sensor-based gait analyses have the potential to support clinical decisions for common musculoskeletal disorders such as osteoarthritis (OA). Additionally, wearable sensors are becoming increasingly popular for the study of OA, with more research utilizing them in out-of-lab gait collections. Unfortunately, much of this work still involves highly controlled and short (e.g., 20m) walking protocols that represent a single snapshot of gait and may not be indicative of the fluctuations occurring daily, real-world gait patterns.
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