Fuzzy Entropy based Complexity Analysis for Target Classification during Hybrid BCI Paradigm-Reference-Cited by-同舟云学术

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Fuzzy Entropy based Complexity Analysis for Target Classification during Hybrid BCI Paradigm

Published:2022-05-26 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on System Science and Engineering (ICSSE)
language:
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Author:

Diddi Sandeep Vara Sankar¹,Ko Li-Wei²

Affiliation:

1. National Yang Ming Chiao Tung University,International Ph.D Program in Interdisciplinary Neuroscience and Center for Intelligent Drug Systems and Smart Biodevices (IDS2B),Hsinchu,Taiwan

2. National Yang Ming Chiao Tung University,International Ph.D. Program in Interdisciplinary Neuroscience, Institute for Bioinformatics and Systems Biology, and the Center for Intelligent Drug Systems and Smart Biodevices (IDS2B),Hsinchu,Taiwan

Funder

Ministry of Science and Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9947350/9947352/09948254.pdf?arnumber=9948254

Reference21 articles.

1. Physiological time-series analysis using approximate entropy and sample entropy

2. Entropy Measures as Descriptors to Identify Apneas in Rheoencephalographic Signals

3. Inherent Fuzzy Entropy for the Improvement of EEG Complexity Evaluation

4. Effects of repetitive ssveps on eeg complexity using multiscale inherent fuzzy entropy;cao;Neurocomputing,2019

5. Characterization of Surface EMG Signal Based on Fuzzy Entropy

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