Wearable sensors based human behavioral pattern recognition using statistical features and reweighted genetic algorithm
Volume: 79, Issue: 9-10, Pages: 6061 - 6083
Published: Dec 12, 2019
Abstract
Human behavior pattern recognition (BPR) from accelerometer signals is a challenging problem due to variations in signal durations of different behaviors. Analysis of human behaviors provides in depth observations of subject’s routines, energy consumption and muscular stress. Such observations hold key importance for the athletes and physically ailing humans, who are highly sensitive to even minor injuries. A novel idea having variant of genetic...
Paper Details
Title
Wearable sensors based human behavioral pattern recognition using statistical features and reweighted genetic algorithm
Published Date
Dec 12, 2019
Volume
79
Issue
9-10
Pages
6061 - 6083
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