Clustering of ECG Signals Based on Fuzzy Neural Network with Initial Weights Generated by Genetic Algorithm

Abstract

Early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through appropriate treatment. Whereas clustering of electrocardiogram (ECG) signals will help to identification of heart diseases as soon as possible. In this regard, neural network and fuzzy logic have been used in many application areas while each of them has advantages and disadvantages. Thus, the present paper utilizes the proposed fuzzy neural network (FNN) with initial weights generated by genetic algorithm (GFNN) for the sake of improvement training speed, accurate and to reduce the chance of the FNN getting stuck on a local minimum.Four types of ECG beats (normal beat, congestive heart failure beat, ventricular tachyarrhythmia beat and atrial fibrillation beat) obtained from the PhysioBank database was clustered by the proposed GFNN model. Model evaluation results indicate that the proposed model can perform more accurately and less training speed than the conventional statistical methods, a single ANN and FNN. The total clustering accuracy of the GFNN model is 98.23%. ØªØ¬ÙÛع إشارات تخطÛØ· اÙÙÙب ÙبÙÛ Ø¹ÙÙ Ø¶Ø¨Ø§Ø¨Û Ø§Ùشبکات اÙعصبÛØ© Ùع اÙØ£Ùزا٠اÙÙبدئÛØ© اÙØªÛ ØªÙ Ø¥ÙشاؤÙا بÙاسطة اÙØ®ÙارزÙÛØ© اÙجÛÙÛةاÙاکتشا٠اÙÙبکر ÙØ£Ùراض اÙÙÙب / تشÙÙات ÛÙک٠أ٠ÛØ·Û٠اÙØ­Ûاة ÙتحسÛÙ ÙÙعÛØ© اÙÙعÛشة ÙÙ Ø®Ùا٠اÙعÙاج اÙÙÙاسب. ÙÛ Ø­Û٠تجÙÛع اÙÚ©ÙØ±Ø¨Ø§Ø¦Û Ù(ECG) إشارات تساعد عÙ٠اÙتعر٠عÙ٠أÙراض اÙÙÙب ÙÛ Ø£Ùرب ÙÙت ÙÙÚ©Ù. ÙÙÛ Ùذا اÙØµØ¯Ø¯Ø ØªÙ Ø§Ø³ØªØ®Ø¯Ø§Ù Ø´Ø¨Ú©Ø§Øª اÙذکاء ÙاÙÙÙط٠اÙØ¶Ø¨Ø§Ø¨Û ÙÛ Ø§ÙعدÛد ÙÙ ÙجاÙات اÙتطبÛÙ ÙÛ Ø­Û٠أ٠ک٠Ùاحد ÙÙÙÙ ÙÙ ÙزاÛا ÙعÛÙب. ÙÙÚ©Ø°Ø§Ø Ùتستخد٠Ùذ٠اÙÙرÙØ© اÙشبکة اÙعصبÛØ© غاÙض اÙÙÙترحة (FNN) Ùع اÙØ£Ùزا٠اÙÙبدئÛØ© اÙØªÛ ØªÙ Ø¥ÙشاؤÙا بÙاسطة اÙØ®ÙارزÙÛØ© اÙجÛÙÛØ© (GFNN) Ù٠أج٠سرعة اÙتدرÛب تحسÛÙ ÙدÙÛÙØ© ÙتÙÙÙ ÙÙ Ùرصة ÙÙFNN Ø£Ù ÛعÙÙÙا عÙÙ Ùا Ùا ÛÙ٠اÙÙØ­ÙÛ.ÙÙد تتجÙع أربعة Ø£ÙÙاع ÙÙ Ûد٠تخطÛØ· اÙÙÙب (ضربات اÙعادÛØ ÙصÙر اÙÙÙب اÙاحتÙاÙÛ ÙÙØ²Ø Ø§ÙبطÛ٠ضربات اضطراب اÙÙظ٠اÙØªØ³Ø±Ø¹Û ÙاÙأذÛÙÛ Ø¶Ø±Ø¨Ø§Øª اÙرجÙاÙ) ت٠اÙحصÙ٠عÙÛÙا ÙÙ Ùاعدة اÙبÛاÙات PhysioBank Ù٠اÙÙÙÙذج GFNN اÙÙÙترحة. ÙتشÛر Ùتائج اÙتÙÛÛ٠اÙÙÙÙذجÛØ© Ø£Ù ÛÚ©Ù٠اÙÙÙÙذج اÙÙÙترح ÛÙÚ©Ù Ø£Ù ØªØ¤Ø¯Û Ø¨Ø´Ú©Ù Ø£Ú©Ø«Ø± دÙØ© ÙØ£Ù٠سرعة اÙتدرÛب Ù٠اÙأساÙÛب اÙإحصائÛØ© اÙتÙÙÛدÛØ©Ø ÙANN Ùاحد ÙFNN. ÙجÙÙع دÙØ© تجÙÛع ÙÙÙذج GFNN ÙÛ 98.23Ùª æå¾çµåç±éä¼ ç®æ³åå§æ模ç³ç¥ç»ç½ç»æ½è±¡æ©æåç°å¿èç¾ç/å¼å¸¸è½å»¶é¿çå½åæé«çæ´»éè¿éå½æ²»ççè´¨éãèå¿çµå¾é群ï¼ECGï¼ä¿¡å·å°å°½å¿«å¸®å©å¿èç¾ççé´å«ãå¨è¿æ¹é¢ï¼ç¥ç»ç½ç»å模ç³é»è¾å·²ç»å¨è®¸å¤åºç¨é¢å中使ç¨ï¼èæ¯ä¸ªäººé½æä¼ç¹å缺ç¹ãå æ­¤ï¼æ¬æå©ç¨ææåºç模ç³ç¥ç»ç½ç»ï¼FNNï¼ä¸éä¼ ç®æ³ï¼GFNNï¼çæçåå§æéæ¹è¿è®­ç»é度ï¼å确起è§ï¼åå°äºæ¨¡ç³ç¥ç»ç½ç»çæºä¼é·å¥ä¸ä¸ªå±é¨æå°ãä»PhysioBankæ°æ®åºä¸­è·å¾åç§ç±»åçå¿çµå¾æ¬¡ï¼æ­£å¸¸è·³å¨ï¼åè¡æ§å¿èè¡°ç«­çè·³å¨ï¼å®¤æ§å¿å¾å¤±å¸¸èå¥åæ¿é¢¤æï¼è¢«æåºGFNN模åé群ã模åçè¯ä¼°ç»æ表æï¼è¯¥æ¨¡åè½æ´åç¡®å°æ§è¡ï¼æ¯ä¼ ç»çç»è®¡æ¹æ³ï¼åä¸ç人工ç¥ç»ç½ç»å模ç³ç¥ç»ç½ç»è®­ç»é度æ´ä½ã该GFNN模åçæ»èç±»åç¡®çæ¯98.23ï¼ã