Comparison of Independent Component Analysis andPrincipal Component Analysis for Artifact Identification inMagneto encephalography Recordings

  • سال انتشار: 1386
  • محل انتشار: ششمین همایش سراسری علوم پایه
  • کد COI اختصاصی: NCSCIE06_060
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 1469
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نویسندگان

Mohammad Asghari Jafarabadi

Dept. of Biostatistics, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran

Ebrahim Hajizadeh

Dept. of Biostatistics, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran

Anooshiravan Kazemnejad

Dept. of Biostatistics, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran

Manoochehr Emadi

Pars Hospital, Tehran, Iran

چکیده

Background: Providing a suitable representation of multivariate data based onlinear transformation is the goal of various fields of researches such as signalprocessing. Methods: For this reason, principal component analysis as a classicaltechnique and independent component Analysis as a new technique, used onMagneto encephalography records, however the optimality of these methods isn tknown for such data. The aim of this article is to compare the two methods andrepresent the optimal technique for Magneto encephalography signal processing inorder to separate the artifacts and noise from brain original signals. Results: Theapplication of these methods on the Magneto encephalography data show thatindependent component Analysis performs very better than principal component analysis and could well separate the muscle activity, saccade related, blinking,respiration and heart rate artifacts and noises from brain original signals.Conclusion: After identification and possible separation and removing of thesesignals, more accurate studies could be done on brain activities.

کلیدواژه ها

Principal Component Analysis, Independent Component Analysis, MEG, Artifact

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