標題: Bio-signal Analysis System Design with Support Vector Machines based on Cloud Computing Service Architecture
作者: Shen, Chia-Ping
Chen, Wei-Hsin
Chen, Jia-Ming
Hsu, Kai-Ping
Lin, Jeng-Wei
Chiu, Ming-Jang
Chen, Chi-Huang
Lai, Feipei
資訊科學與工程研究所
Institute of Computer Science and Engineering
公開日期: 1-Jan-2010
摘要: Today, many bio-signals such as Electroencephalography (EEG) are recorded in digital format. It is an emerging research area of analyzing these digital bio-signals to extract useful health information in biomedical engineering. In this paper, a bio-signal analyzing cloud computing architecture, called BACCA, is proposed. The system has been designed with the purpose of seamless integration into the National Taiwan University Health Information System. Based on the concept of. NET Service Oriented Architecture, the system integrates heterogeneous platforms, protocols, as well as applications. In this system, we add modern analytic functions such as approximated entropy and adaptive support vector machine (SVM). It is shown that the overall accuracy of EEG bio-signal analysis has increased to nearly 98% for different data sets, including open-source and clinical data sets.
URI: http://dx.doi.org/10.1109/IEMBS.2010.5626713
http://hdl.handle.net/11536/146288
ISSN: 1557-170X
DOI: 10.1109/IEMBS.2010.5626713
期刊: 2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
起始頁: 1421
結束頁: 1424
Appears in Collections:Conferences Paper