A Comparative Study of Different Feature Extraction Methods for Motor Imagery EEG Decoding within the Same Upper Extremity
文献类型：会议论文
| 作者 | Zou YJ(邹宜君)1,2,3 ; Zhao YW(赵忆文)1,2; Xu WL(徐卫良)1,4; Zhang, He5; Zhao XG(赵新刚)1,2; Chu YQ(褚亚奇)1,2,3
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| 出版日期 | 2018 |
| 会议日期 | November 30 - December 2, 2018 |
| 会议地点 | Xi'an |
| 关键词 | brain-computer interfaces motor imagery EEG same upper extremity feature extraction common spatial patterns |
| 页码 | 330-335 |
| 英文摘要 | Compared to other electroencephalogram (EEG) modalities, motor imagery (MI) based brain-computer interfaces (BCIs) can provide more natural and intuitive communication between human intentions and external machines. However, this type of BCI depends heavily on effective signal processing to discriminate EEG patterns corresponding to various MI tasks, especially feature extraction procedures. In this study, a comparison of different feature extraction methods was conducted for EEG classification of imaginary movements within the same upper extremity. Unlike traditional MI tasks (left/right hand), six imaginary movements from the same unilateral upper extremity were proposed and evaluated, including elbow flexion/extension, forearm supination/pronation, and hand grasp/open. To tackle the classification challenge of MI tasks within the same limb, four types of feature extraction methods were implemented and compared in combination with support vector machine (SVM) and linear discriminant analysis (LDA) classifiers, such as wavelet transformation, power spectrum, autoregressive model, common spatial patterns (CSP) and variants of filter-bank CSP (FBCSP), regularized CSP (RCSP). The overall accuracies of the CSP were significant higher than other three types of feature extraction on a dataset collected from 8 individuals, particularly the SVM with FBCSP had the best performance with an average accuracy of 71.78%. These decoding results of MI tasks during single upper extremity are encouraging and promising in the context of more natural MI-BCI for controlling assisted devices, such as a neuroprosthetic or robotic arm for motor disabled individuals with highly impaired upper extremity. |
| 产权排序 | 1 |
| 会议录 | 2018 Chinese Automation Congress (CAC)
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-1312-8 |
| WOS记录号 | WOS:000459239500063 |
| 源URL | [http://ir.sia.cn/handle/173321/23838]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Chu YQ(褚亚奇) |
| 作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), Shenyang, Liaoning, 110016, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences (CAS) 3.University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China 4.Department of Mechanical Engineering, University of Auckland, Auckland, 1142, New Zealand 5.Department of Orthopedics, Xinqiao Hospital, Third Military Medical University, Chongqing, 400038, China |
| 推荐引用方式 GB/T 7714 | Zou YJ,Zhao YW,Xu WL,et al. A Comparative Study of Different Feature Extraction Methods for Motor Imagery EEG Decoding within the Same Upper Extremity[C]. 见:. Xi'an. November 30 - December 2, 2018. |
入库方式： OAI收割
来源：沈阳自动化研究所
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