{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/120269"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/120269","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Analysis of a shuffling detection device for fall prevention","abstract":"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.","abstract_html":"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. 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