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基于频带能量和相同步的运动意识任务分类研究 被引量：3

Study on Classification of Imaginary Hand Movements Based on Band Power and Phase Synchronization
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摘要 提出了基于信号频带能量和相同步作为脑电特征向量,实现对左右手运动意识任务的分类方法.用线性判别式算法对左右手运动想象脑电模式进行识别,识别正确率最高达到了86.43%,与只用特定频带能量作为脑电特征分类结果相比,效果更好.为大脑运动意识任务的分类提供了新思路. A method for single trial on-line classification of imaginary hand movements, based on band power and phase synchronization derived from EEG, is proposed. The event-related EEG patterns during left and right hand motor imagery are identified by using the linear discriminant algorithm. The results show that the method is effective and the correct rate of classification is up to 86.43 %. It might provide a new way for the classification of mental tasks.
作者 张爱华 任亚莉 郝晓弘
机构地区 兰州理工大学电气工程与信息工程学院 陇东学院物理与电子工程学院
出处 《甘肃科学学报》 2008年第2期75-78,共4页 Journal of Gansu Sciences
基金 甘肃省高等学校研究生导师科研项目(0710-05) 兰州理工大学博士基金(SB03200702)
关键词 脑电信号 频带能量 相同步 特征提取 分类 EEG band power phase synchronization feature extraction classification
分类号 R318 [医药卫生—生物医学工程]
作者简介 张爱华（1964-）女，河北省永年人，2005年毕业于西安交通大学生物医学工程专业获博士学位，现任兰州理工大学电气工程与信息工程学院教授．研究方向：生物医学信号检测、处理与识别．
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参考文献10

  • 1Guest Editorial. Brain-Computer Interface Technology: Areview of the Second International Meeting [J]. IEEE Trans. Neural Systems and Rehab, 2003,11 (2) : 94-109.
  • 2P Sykacek, S J Roberts, M Stokes. Adaptive BCI Based on Variational Bayessian Kalman Filtering:An Empirical Evaluation[J]. IEEE Transaction on Biomedical Engineering, 2004, 17(5):57-64.
  • 3J Deng, B He. Classification of Imaginary Tasks from Three Vhannels of EEG by Using an Artificial Neural Network[A]. Proc. of the 25 th Annual International Conference of the IEEE/EMBS[C]. Cancun Mexico: IEEE,2003,2 289-2 291.
  • 4李坤,褚蕾蕾,朱世东,吴小培.基于mu节律能量的运动意识分类研究[J].计算机技术与发展,2006,16(8):157-159. 被引量：18
  • 5张爱华,赵予晗.相同步及支持向量机在意识任务识别中的应用[J].甘肃科学学报,2006,18(3):59-63. 被引量：7
  • 6吴小培,叶中付.基于脑电四阶累积量的运动意识分类研究[J].生物物理学报,2005,21(5):364-370. 被引量：11
  • 7Schlogl A, Lugger K, Pfurtscheller G. Using Adaptive Autoregressive Parameters for a Brain-Computer -Interface Experiment[A]. Proceedings of the 19th Annual International Conference IEEE/EMBS[C]. 1997,19:1533-1535.
  • 8Pfurtscheller G, Neuper Ch, Sehlogl A, et al. Separability of EEG Siganls Recorded During Rigth and Left Motor Imagery Using Adaptive Autoregressive Parameters[J]. IEEE Trans. Rehab. Eng. ,1998,6(3) :316-25.
  • 9J A Pineda,B Z Allison,A Vankov. The Effects of Self-movement, Observation, and Imagination on Mu Rhythms and Readiness Potentials(RP's) : Toward a Brain-computer Interface[J]. IEEE Trans. Rehab. Eng. , 2000,8 : 219-222.
  • 10Pikovsky A S, Volkmann J, Schnitzler A, et al. Detection of n : m Phase Locking from Noisy Data[J]. Application to Magneto Encephalography,Phys Rev Lett, 1998,3 291-3 294.

二级参考文献24

  • 1边肇祺.模式识别[M].北京：清华大学出版社,1998..
  • 2Eleanor A. Currana,b and Maria J. Stokesa, Learning to control brain activity: A review of the produc- tion and control of EEG components for driving brain-computer interface (BCI)systems. Brain and cognition, 2003,51(3):326-336.
  • 3Pfurtscheller G, Aranibar A. Event-related cortical desynchronization detected by power measurements of scalp EEG.Electroencephalography and Clinical Neurophysiology, 1977,42(8):817-826.
  • 4Pfurtscheller G, Neuper C. Motor imagery and direct brain-computer communication. Proceedings of IEEE, 2001,89(7): 1123-1134.
  • 5Keirn ZA, Aunon JI. A New Mode of Communication Between Man And His Surroundings. IEEE Transactions on Biomedical Engineering, 1990,37(12):1209-1214.
  • 6Schloegl A, Lugger K, Pfurtscheller G. Using adaptive autoregressive parameters for a brain-computer-interface experiment. Proceedings of 19th International Conference IEEE/EMBS. 1997:1533-1535.
  • 7Pfurtscheller G, Neuper C, Muller GR. Graz-bci: state of the art and clinical applications. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2003,11(2):177-180.
  • 8Wolpaw JR, McFarland DJ, Vaughan TM. Brain-computer interface research at the Wadsworth Center. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2000,8(2):222-226.
  • 9Wolpaw J R,Birbaumer N,McFarland D J.Brain-computer interfaces for communication and control[J].Clinical Neurophysiology,2002,113:767-791.
  • 10Hinterbergera T,Kiiblera A.A brain-computer interface (BCI) for the locked-in:comparison of different EEG classifications for the thought translation device[J].Clinical Neurophysiology,2003,114:416-425.

共引文献21

同被引文献16

引证文献3

二级引证文献5

甘肃科学学报
2008年 第2期

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