earticle

논문검색

Research on EEG Recognition Algorithm Based on SVM Classifier

초록

영어

As more and more insight into the human brain, EEG is not only for application, processing and analysis of EEG in science and engineering field, it will also be very important in the physical, psychological and pathological studies in humans. The EEG brain - machine interface technologies to achieve the human brain and the computer or other human interface devices to communicate and control, it can provide a special kind of information exchange and live entertainment, is also disabled and a new way of control. In this paper, the collection of information preprocessing electroencephalogram (EEG) signals is proposed wavelet packet transform feature extraction method, using SVM classifier, classification based on the operation mode to achieve recognition of the EEG signal. For different individuals turn, the next turn, show fist, fist four kinds of hand motion recognition experiments show that the average recognition rate of over 80%, significantly better than the other methods to identify results.

목차

Abstract
 1. Introduction
 2. EEG-Based Brain-Computer Interface System
 3. EEG Definition
  3.1. EEG Data Acquisition
  3.2. Pretreatment EEG
 4. EEG Feature Extraction
  4.1. Wavelet Transform Theory
  4.2. Wavelet Transform Theory
 5. SVM EEG Classification
  5.1. Data Test Results
 6. Conclusion
 References

저자정보

  • Zhang Chao Chang Chun University, Chang Chun, China
  • Zhao Xilu Saitama Institute of Technology, Saitama, Japan
  • Pan Su Department of Orthopedics, the Second Hospital of Jilin University, Changchun, China
  • Yang Yudan China-Japan Union Hospital, Jilin University, Changchun, China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.