Human Activity Recognition Based on the Hierarchical Feature Selection and Classification Framework

@article{Zheng2015HumanAR,
  title={Human Activity Recognition Based on the Hierarchical Feature Selection and Classification Framework},
  author={Yuhuang Zheng},
  journal={J. Electrical and Computer Engineering},
  year={2015},
  volume={2015},
  pages={140820:1-140820:9}
}
Human activity recognition via triaxial accelerometers can provide valuable information for evaluating functional abilities. In this paper, we present an accelerometer sensor-based approach for human activity recognition. Our proposed recognition method used a hierarchical scheme, where the recognition of ten activity classes was divided into five distinct classification problems. Every classifier used the Least Squares Support VectorMachine (LS-SVM) andNaive Bayes (NB) algorithm to distinguish… CONTINUE READING

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