Fall detection system for elderly people
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abstract
accelerometer and a 3-axis gyroscope to measure linear acceleration and angular velocities, respectively.
Information from both sensors is used to characterize movements through selected features extracted from
raw data. A classification system based on a Feedforward Backpropagation Neural Network is then trained,
based on the extracted features. The performed tests present low false positives and low false negatives rates
with good specificity and sensitivity values.