Dr. Jun Ma Profile

Dr. Jun Ma

at Shanghai Univ

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 11 November 2021 Paper

EEG unilateral limb motor imagery modeling based on fMRI screening

Jun Ma, Wen Wang, Wenzheng Qiu, Banghua Yang

Proceedings Volume 12076, 1207605 (2021) https://doi.org/10.1117/12.2607836

KEYWORDS: Electroencephalography, Functional magnetic resonance imaging, Brain, Neuroimaging, Data modeling, Statistical analysis, Brain activation, Visualization, Neural networks, Convolution

Read Abstract +

Motor imagery brain computer interface (MI-BCI) recognizes brain motor intention through electroencephalogram (EEG) acquisition and deep learning. The advantage of MI-BCI is that the recognition of brain ideas does not depend on task prompts, but it is difficult to accurately recognize the unilateral limb motor imagery tasks because of the difficulty of EEG decoding algorithm. In this paper, the asynchronous functional magnetic resonance imaging (fMRI) and EEG motor imagery data of unilateral limb hand grasping and hand handling tasks are creatively collected, and the brain activation features of each task are obtained by fMRI statistical analysis. The activation difference of the fMRI cerebral cortex is mapped to the corresponding channel position of the corresponding EEG and compared with the average power spectrum density (PSD) of each channel of each EEG trail. According to the comparison results, the more consistent EEG data are selected for training. The experimental results show that the screened EEG data training model shows a predict accuracy of 69.3%, which is a better classification result. The results proved that screening high-quality EEG by fMRI data has a certain effect, and the model is more consistent with the characteristics of brain motor imagery. This method can improve the prediction accuracy and guide the subjects to imagine correctly.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years