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Journal Article
Research Support, Non-U.S. Gov't
Assessment of waist-worn tri-axial accelerometer based fall-detection algorithms using continuous unsupervised activities.
This study aims to evaluate a variety of existing and novel fall detection algorithms, for a waist mounted accelerometer based system. Algorithms were tested against a comprehensive data-set recorded from 10 young healthy subjects performing 240 falls and 120 activities of daily living and 10 elderly healthy subjects performing 240 scripted and 52.4 hours of continuous unscripted normal activities.
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