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December 1, 2019Open Access

뇌파 기반 감정 분류: 조사

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Abstract

초록 뇌파 감정 분석은 현재 감정 분석의 가장 혁신적인 방법입니다. 뇌 과학의 발전에 따라 인간의 감정이 뇌에서 비롯된다는 사실이 밝혀졌습니다. 그 결과, 많은 뇌파 감정 관련 응용 프로그램이 등장했습니다. 그러나 뇌파 감정 분석은 인간 감정의 복잡성으로 인해 분석의 어려움을 증가시킵니다. 많은 연구자들이 다양한 분류 방법을 사용하고 뇌파 감정 분류를 위한 방법을 제안했습니다. 본 논문에서는 기존의 뇌파 감정 분류 방법을 조사하고 다양한 분류 방법을 설명합니다.

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Authors

Ting-Mei Li

National Dong Hwa University

Han‐Chieh Chao

Tamkang University

Jianming Zhang

Second Affiliated Hospital of Zhejiang University

Journals

Human-centric Computing and Information Sciences

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Institutions

Changsha University of Science and Technology

National Dong Hwa University

National Ilan University

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Li et al. (Sun,)은 이 질문을 연구했습니다.

synapsesocial.com/papers/6a15be86814bf8ec9a4efe5f — DOI: https://doi.org/10.1186/s13673-019-0201-x

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2010 Annual International Conference of the IEEE Engineering in Medicine and Biology· 2010 · 62 citations
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The Nature of Statistical Learning Theory· 2000 · 10,652 citations
Comparison of different wavelet features from EEG signals for classifying human emotions· 2009 · 53 citations

Also consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology· 2010 · 62 citations
A Novel Signal Modeling Approach for Classification of Seizure and Seizure-Free EEG Signals· 2018 · 169 citations
EEG feature extraction for classifying emotions using FCM and FKM· 2008 · 139 citations
The Nature of Statistical Learning Theory· 2000 · 10,652 citations
Comparison of different wavelet features from EEG signals for classifying human emotions· 2009 · 53 citations

뇌파 기반 감정 분류: 조사

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

Cite this study

Also consider

Also consider