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From the original data, prototype, app-based versions of FallCall Detect were built. All parts of the fall detection algorithm were set and controlled fall testing was conducted. After hundreds more falls from the sitting and standing positions were conducted, it was observed that over 80% of falls could be detected with average high vs. low accuracy determination ranging from 60% + to 80%+. From additional experiments, our team defined algorithm adjustments that were necessary to minimize false activations while still being able to detect and differentiate falls.
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