Validation of automated mobility assessment using a single 3D sensor

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Abstract

Reliable mobility assessment is essential to diagnose or optimize treatment in persons affected by mobility disorders, e.g., for musculo-skeletal disorders. In this work, we present a system that is able to automatically assess mobility using a single 3D sensor. We validate the system ability to assess mobility and predict the medication state of Parkinson’s disease patients while using a relatively small number of motion tasks. One key component of our system is a graph-based feature extraction technique that can capture the dynamic coordination between parts of the body while providing results that are easier to interpret than those obtained with other data-driven approaches.We further discuss the system and the study design, highlighting aspects that provide insights for developing mobility assessment applications in other contexts.

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Kao, J. Y., Nguyen, M., Nocera, L., Shahabi, C., Ortega, A., Winstein, C., … Bacon, H. (2016). Validation of automated mobility assessment using a single 3D sensor. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9914 LNCS, pp. 162–177). Springer Verlag. https://doi.org/10.1007/978-3-319-48881-3_12

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