نوع مقاله : مقاله کامل پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد بیوالکتریک، گروه مهندسی پزشکی، دانشگاه سمنان، سمنان

2 استادیار، گروه مهندسی پزشکی، دانشگاه سمنان، سمنان

10.22041/ijbme.2016.20227

چکیده

قلب انسان سیستمی آشوبناک است؛ از­این­رو برای شناسایی انواع آریتمی‌های قلبی از بعد فرکتال استفاده می­شود. آریتمی‌های قلبی یکی از شایع‌ترین بیماری‌ها هستند که شناسایی آن‌ها بسیار مهم است. نمای هورست معیاری برای ارزیابی میزان آشوبناکی سیستم‌ها و کمی‌سازی بعد فرکتال سیستم‌های آشوبناک است، که با روش تحلیل دامنة بازمقیاس محاسبه می‌شود. براساس مطالعات انجام شده، نمای هورست کلاسیک ویژگی مناسبی برای طبقه‌بندی آریتمی‌های قلبی نیست؛ زیرا از یک­سو، انتخاب و تعیین مقدار پارامترها به­شدت بر مقدار محاسبه شده برای نمای هورست تاثیر می‌گذارد و از سوی دیگر، این روش وابستگی بسیاری به نرخ ضربان قلب دارد. در این مقاله، شاخص هورست چندگانة اصلاح شده برای طبقه‌بندی آریتمی‌های قلبی پیشنهاد­شده است که نسبت به نمای هورست کلاسیک، ویژگی‌های مناسب‌تری برای طبقه‌بندی آریتمی‌های قلبی فراهم می‌سازد و نسبت به تغییرات نرخ ضربان قلب نیز مقاوم است. بررسی‌های انجام شده با استفاده از این روش روی 80 سیگنال، شامل ریتم نرمال و آریتمی‌های انسداد دستة‌ شاخة راست (RBBB)، انسداد دستة شاخة چپ (LBBB) و انقباض زودرس دهلیزی(APC) از پایگاه دادة MIT-BIH، توانسته است با استفاده از طبقه‌بندی‌کننده‌های LDA ، نزدیک‌ترین همسایه و شبکة عصبی به­ترتیب به صحت طبقه‌بندی 75/88 %، 25/96 % و 100 % منجر شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Modified Multiple Hurst Index for Evaluating Measure of Chaoticity in Cardiac Arrhythmias Classification Application

نویسندگان [English]

  • Mina Hemmatian 1
  • Ali Maleki 2

1 Msc Student, Biomedical Engineering Department, Semnan University, Semnan, Iran

2 Assistant Professor, Biomedical Engineering Department, Semnan University, Semnan, Iran

چکیده [English]

The humans’ heart is a chaotic system so use of fractal dimension to identify cardiac arrhythmias has been considered. Cardiac arrhythmias are prevalent diseases that is very important to be diagnosed. Hurst index which is calculated using rescaled range analysis method, is used as a criterion to evaluate chaotic systems and to quantify the fractal dimensions. Previous studies have shown that classical Hurst index is not appropriate for classification of cardiac arrhythmias because not only selection of algorithm parameters affect the value of determined Hurst index, but also it significantly varies as the heart rate changes. In this paper, modified multiple Hurst index has been proposed to classify the cardiac arrhythmias. The presented index is resistant against changes in heart rate and can be used to identify appropriate features to classify the cardiac arrhythmias. 80 signal from four types of ECG beats obtained from the MIT-BIH Arrhythmia dataset has been used to validate the algorithm. Results show that this method is able to detect normal rhythm and right bundle branch block (RBBB), left bundle branch block (LBBB) and atrial premature complex (APC) arrhythmias with accuracy of 100%, 96.25% and 88.75% using artificialneural network, k nearest neighbor and LDA classifiers respectively.

کلیدواژه‌ها [English]

  • chaos
  • fractal dimension
  • cardiac arrhythmia classification
  • Hurst Exponent
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