GA-based Feature Subset Selection for Myoelectric Classification

@article{Oskoei2006GAbasedFS,
  title={GA-based Feature Subset Selection for Myoelectric Classification},
  author={Mohammadreza Asghari Oskoei and Huosheng Hu},
  journal={2006 IEEE International Conference on Robotics and Biomimetics},
  year={2006},
  pages={1465-1470}
}
This paper presents an ongoing investigation to select optimal subset of features from set of well-known myoelectric signals (MES) features in time and frequency domains. Four channel of myoelectric signal from upper limb muscles are used in this paper to classify six distinctive activities. Cascaded genetic algorithm (GA) has been adopted as the search strategy in feature subset selection. Davies-Bouldin index (DBI) and Fishers linear discriminant index (FLDI) are employed as the filter… CONTINUE READING
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