A Novel Method of Building Functional Brain Network Using Deep Learning Algorithm with Application in Proficiency Detection

International Journal of Neural Systems
Chengcheng HuaSyed Madiha Khalid

Abstract

Functional brain network (FBN) has become very popular to analyze the interaction between cortical regions in the last decade. But researchers always spend a long time to search the best way to compute FBN for their specific studies. The purpose of this study is to detect the proficiency of operators during their mineral grinding process controlling based on FBN. To save the search time, a novel semi-data-driven method of computing functional brain connection based on stacked autoencoder (BCSAE) is proposed in this paper. This method uses stacked autoencoder (SAE) to encode the multi-channel EEG data into codes and then computes the dissimilarity between the codes from every pair of electrodes to build FBN. The highlight of this method is that the SAE has a multi-layered structure and is semi-supervised, which means it can dig deeper information and generate better features. Then an experiment was performed, the EEG of the operators were collected while they were operating and analyzed to detect their proficiency. The results show that the BCSAE method generated more number of separable features with less redundancy, and the average accuracy of classification (96.18%) is higher than that of the control methods: PLV (92.19%) and...Continue Reading

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Citations

Mar 3, 2020·International Journal of Neural Systems·Yongjie ZhuFengyu Cong
Jul 31, 2020·International Journal of Neural Systems·A ApicellaG Tamburrini
Aug 14, 2020·International Journal of Neural Systems·Diego Castillo-BarnesJuan M Górriz
Sep 18, 2020·International Journal of Neural Systems·Pankaj MishraGian Luca Foresti
Sep 18, 2020·International Journal of Neural Systems·Hiroaki HashimotoMasayuki Hirata
Apr 21, 2020·International Journal of Neural Systems·Matthew LemingJohn Suckling
Sep 1, 2020·Reviews in the Neurosciences·Hidir Selcuk Nogay, Hojjat Adeli
Nov 18, 2020·International Journal of Neural Systems·Danilo AvolaGian Luca Foresti
Aug 12, 2021·International Journal of Neural Systems·Cosimo IeracitanoNadia Mammone
Feb 13, 2021·International Journal of Neural Systems·Petr HajekMichal Munk
Mar 24, 2021·International Journal of Neural Systems·David Bricher, Andreas Müller

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