Analysis of a shuffling detection device for fall prevention
Author(s)Alexander, Alaisha (Alaisha Diahann)
Massachusetts Institute of Technology. Department of Mechanical Engineering.
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According to the World Health Organization, falls are the second leading cause of accidental or unintentional injury deaths worldwide. In order to address this issue from a fall prevention perspective, I began developing a footwear device to give feedback to the user on their walking. In this iteration, I've identified characteristics to distinguish between shuffling and walking strides for implementation in a threshold-based algorithm and the device created was effective in making this distinction with a 74.65% accuracy and 73.17% sensitivity. The errors identified are those common to threshold-based algorithms and can be corrected in future iterations with a more sensitive threshold and stride detection method. Moving forward, the device can be improved in order to be integrated into a feedback device for the intended user.
Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (page 16).
DepartmentMassachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology