Sammanfattning

A new approach for recognizing single-channel EEG pattern induced by acupuncture on acupoint of Zusanli was presented. EEG was decomposed by ensemble empirical mode decomposition (EEMD) into a small number of intrinsic mode functions (IMFs) based on intrinsic local characteristic time scale. The power, standard deviation, and analytic amplitude of first two IMFs expressed the difference between normal EEG and EEG affected by acupuncture. The two EEG patterns could be classified by extreme learning machine (ELM) with faster and better classification performance compared with BP. Similar classification accuracy of different channels indicated the global EEG pattern affected by acupuncture.

Publicerad i

Advances in cognitive neurodynamics
2016, nummer: 5, sidor: 485-491
Titel: Advances in Cognitive Neurodynamics (V)
ISBN: 978-981-10-0207-6
Utgivare: Springer

SLU författare

• Liljenström, Hans

  • Institutionen för energi och teknik, Sveriges lantbruksuniversitet
    

UKÄ forskningsämne

Signalbehandling


Publikationens identifierare

DOI: https://doi.org/10.1007/978-981-10-0207-6_66

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/73834