The Automatic Detection of Artifacts in Magnetoencephalographic Signals Based on Fast ICA
As a non-invasive technique applied for the functional mapping of human brain, Magnetoencephalography (MEG) can acquire the neural activity with high temporal resolution and moderate spatial resolution. However, when reading a MEG record, for research or clinical reference, the investigator face the signals from non-cerebral sources like eye movements, heart beat and muscle activity always appear mixed with brain signals. In this article, we proposed a procedure including the independent component analysis(ICA) followed by an automatic independent component(IC) detection module mainly based on the analysis of statistical and spectral characteristics of each IC to remove the artifacts from MEG signals. The whole process was tested with both simulated data and real MEG signal, the results showed that the proposed technique was able to differentiate artfactual ICs successfully.
Artifact rejection Independent Component Analysis Magnetoencephalography
Yu-Peng Liao Ping Zhou Shi-Ping Xie Wei Yan Zhong-Dang Xiao Ning-Ping Huang
State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southe Nanjing Med Univ, Nanjing Brain Hosp, Acad Dept Psychiat, Nanjing, 210096, P.R. China
国际会议
上海
英文
864-868
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）