Convolutional Neural Network for Resting State EEG Signal Analysis

Liu, Hongyu; He, Lianghua; Shang, Shaohua; Lu, Jian; Wan, Meng; Liu, Shuang

doi:10.1109/icnsc.2019.8743338

2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC) 2019

DOI: 10.1109/icnsc.2019.8743338

|View full text |Cite

Convolutional Neural Network for Resting State EEG Signal Analysis

Hongyu Liu

Lianghua He

Shaohua Shang

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A Novel Method for Gender and Age Detection Based on EEG Brain Signals

Issa¹,

Issa²,

Shah³

2021

IAJIT

View full text Add to dashboard Cite

This paper presents a new gender and age classification system based on Electroencephalography (EEG) brain signals. First, Continuous Wavelet Transform (CWT) technique is used to get the time-frequency information of only one EEG electrode for eight distinct emotional states instead of the ordinary neutral or relax states. Then, sequential steps are implemented to extract the improved grayscale image feature. For system evaluation, a three-fold-cross validation strategy is applied to construct four different classifiers. The experimental test shows that the proposed extracted feature with Convolutional Neural Network (CNN) classifier improves the performance of both gender and age classification, and achieves an average accuracy of 96.3% and 89% for gender and age classification, respectively. Moreover, the ability to predict human gender and age during the mood of different emotional states is practically approved.

show abstract

A Novel Method for Gender and Age Detection Based on EEG Brain Signals

Issa¹,

Issa²,

Shah³

2021

IAJIT

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Convolutional Neural Network for Resting State EEG Signal Analysis

Cited by 1 publication

References 14 publications

A Novel Method for Gender and Age Detection Based on EEG Brain Signals

A Novel Method for Gender and Age Detection Based on EEG Brain Signals

Contact Info

Product

Resources

About