کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
384307 660843 2010 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparative clustering analysis of bispectral index series of brain activity
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Comparative clustering analysis of bispectral index series of brain activity
چکیده انگلیسی

Bispectral index scale (BIS) is a continuous processed electroencephalogram (EEG) parameter that correlates to the patient’s level of brain activity, where 100 is awake and 0 (flat line) is dead. BIS was designed to correlate with “hypnotic” clinical endpoints (sedation, lack of awareness, and memory) and to track changes in the effects of anesthetics on the brain. In this study, an approach to utilize clustering methods is investigated in the analysis of BIS series data. Fuzzy c-Means (The FCM) and Fuzzy Neighborhood DBSCAN (FN-DBSCAN) algorithms are handled in the paper. The FN-DBSCAN algorithm is advantageous in such a way that it aggregates the speed of the well-known Density Based Spatial Clustering of Applications with Noise (DBSCAN) and the robustness of the Noise-Robust Fuzzy Joint Points (NRFJP) algorithms. As a result of the computational experiments, we can conclude that FN-DBSCAN method gives more realistic results to recognize the stable duration intervals and the BIS stages in the measurement series.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 37, Issue 3, 15 March 2010, Pages 2495–2504
نویسندگان
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