Comparison of Independent Component Analysis andPrincipal Component Analysis for Artifact Identification inMagneto encephalography Recordings
Publish place: 6th National Conference on Science
Publish Year: 1386
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
NCSCIE06_060
تاریخ نمایه سازی: 11 شهریور 1391
Abstract:
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.
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Authors
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