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Extending free living gait analysis: A pilot study towards multi modal sensing

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Background: Various technologies are used to digitalise human walking (gait) using quantitative data. Motion capture systems, instrumented walkways, and force platforms are perceived as the reference standards in gait assessment, but are costly and have low accessibility. Wearable devices (inertial measurement units, IMUs) are effective and affordable to assess gait with additional advantages such as use during free-living for extended periods of time (e.g. a day). Spatial and temporal outcomes along with kinetic, kinematic, and muscle functionality are widely used gait characteristics to describe impaired gait and may indicate specific biomechanical deficits. However, the number of studies that investigates multiple gait characteristics is limited due to the complexities of using multiple technologies. Therefore, existing conceptual gait models used to ease the understanding of the complexities in neurological gait assessment by detailing gait domains (e.g. pace) with subcategories of characteristics (e.g. step time), are limited to IMU-based spatiotemporal outcomes.

Aim: To improve current conceptual gait models using multi-modal wearable sensing (IMU-Electromyography (EMG)).

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