A rusboosted tree method for k-complex detection using tunable q-factor wavelet transform and multi-domain feature extraction

HIGHLIGHTS

  • who: Yabing Li from the Xi`an University of Science and Technology, China have published the research: A RUSBoosted tree method for k-complex detection using tunable Q-factor wavelet transform and multi-domain feature extraction, in the Journal: (JOURNAL)
  • what: In this study, to develop and present a procedure of kcomplex detection in an epoch, a robust method for the imbalance dataset was proposed based on TQWT coupled with the RUSBoosted tree classifier. The multi-domain features based on the analysis of the EEG signals were employed to represent k-complex and non-kcomplex . . .

     

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