In this paper, we present a neural network-based approach to classify the activities performed by 40 subjects by analyzing sub-bandage pressure signals. The approach includes an input dimensionality reduction obtained employing both feature extraction and feature selection techniques. The results show that our model is able to classify the activities performed with 98.12% accuracy.
Physical activity recognition from sub-bandage sensors using both feature selection and extraction
P Salvo
2017
Abstract
In this paper, we present a neural network-based approach to classify the activities performed by 40 subjects by analyzing sub-bandage pressure signals. The approach includes an input dimensionality reduction obtained employing both feature extraction and feature selection techniques. The results show that our model is able to classify the activities performed with 98.12% accuracy.File in questo prodotto:
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