同步腦機介面特徵分析與研究

潘彥霖

doi:10.6840/cycu201000711

3.235.25.27，Hello！

Close
Search Quick Search Advanced Search Publication Search	Personal Service Member Login Searching History Use Bonus Card SYMSKAN
Browse Browse by University of Graduate Thesis Browse by Pinyin of Graduate Thesis Browse by Conference Proceedings Topic Browse by Conference Proceedings Publisher Browse by Pinyin of Conference Proceedings Browse by eBook Category Browse by eBook Topic Browse by eBook Publisher
Customer Services Authorize Airiti Recommend a Journal

Search Symbol (Half-width)	Description of Search Symbols
Space	"AND" indicates the intertwining of key terms used in a search
Double Quotation Marks ("") ( " " )	Double quotation marks indicate the beginning and end of a phrase, and the search will only include terms that appear in the same order of those within the quotations. Example: "image process" ： " image process "
?	Indicates a variable letter. Entering two ? will indicate two variable letters, and so on. Example: "Appl?", search results will yield apple, apply… e , appl y … ( (often used to English word searches) )
*	Indicates an unlimited number of variable letters to follow, from 1~n. Example: Enter "appl*", search results will yield apple, apples, apply, applied, application…(often used in English word searches) e , appl es , appl y , appl ied , appl ication … ( (often used to English word searches) )
AND、OR、NOT	Boolean logic combinations of key words is a skill used to expand or refine search parameters. (1) AND (1) AND: Refines search parameters (2) OR (2) OR: Expands search parameters (3) NOT: Excludes irrelevant parameters

DOI stands for Digital Object Identifier （ D igital O bject I dentifier ） ,
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.

Using DOI as a persistent link

To create a persistent link, add「http://dx.doi.org/」「 http://dx.doi.org/ 」 before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.

Cite a document with DOI

When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.

DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ）。

Data Source

College of Engineering > Department of Mechanical Engineering
Engineering > Mechanical Engineering

Bibliography Management Tool

Related Links

Report an Issue

Purchase Single Articles

Download PDF

同步腦機介面特徵分析與研究

Analysis of Synchronous BCI Features and Studies

潘彥霖 , Masters　　Advisor：劉益宏　　

繁體中文 DOI： 10.6840/cycu201000711

自迴歸模型；功率頻譜熵值；共同空間型態；支持向量機器；同步化系統；腦機介面； Autoregressive Model ； Power Spectral Entropy ； Support Vector Machine ； Common Spatial Pattern ； Synchronous system ； Brain Computer Interface

Abstract │ Reference (106) │ Altmetrics

Abstract 〈TOP〉

Parallel Abstract 〈TOP〉

The researches on analysis of biosignal related areas have received increasingly attention in recently years because the skills of technical computing promotion and the analysis method improvement. Brain-computer interface (BCI) is one of the novelty skills. The main purpose of BCI is to use the variation of electroencephalogram (EEG) signals and the user can use them to communicate with the external environment directly.

The main purpose of this thesis is to build the synchronous system to analyze the variation of EEG signals in somatosensory cortex area when the subject made different kinds of motor imagery (imagined right-hand or left-hand movements) experiments (or real hand movements). Then, we chose the most discriminated EEG signals from the specific frequency band as the recognition datasets and used them to classify. We used the finite impulse response (FIR) filter to reduce the ambient noises and some of physiological signals in signal preprocessing. We used Common Spatial Pattern (CSP) method to do a linear transform and extracted the discriminative features on time and frequency domain, respectively. In the feature extraction methods, we used Autoregressive Model (ARM) and Power Spectral Entropy (PSE) to extract the features and found the most discriminative features to classify. Finally, we used K Nearest Neighbor classifier (K-NN) and Support Vector Machine (SVM) to classify these features and made the comprehensive comparison.

The experimental results show the classification rates in different motor imagery tasks all can reach over 70 % when using the ARM as the feature extraction method and SVM as the classifier. The classification rate in the imagined finger movement task can even achieve 80%.

Reference ( 106 ) 〈TOP〉

[2] 方振隆，“以腦波控制之主動式義手，” 國立成功大學機械工程學系碩士論文，2004。
連結：
[4] 堺章，“透視人體醫學地圖，” 瑞昇文化事業股份有限公司，2008年。
連結：
assessing the speed of a P300-based brain-computer interface,” IEEE
連結：
Transactions on Rehabilitation Engineering, vol. 8, pp. 174-179, June
連結：
filtering of single trial EEG during imagined hand movement,” IEEE
連結：

Altmetrics

〈TOP〉

E-mail ：

When an article is available to download, a notice will be sent to your mailbox address.

E-mail ：