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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Current Result Document : 13 / 28 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) Á¶±â½É½Ç¼öÃà(PVC) ºÐ·ù¸¦ À§ÇÑ È¯ÀÚ ÀûÀÀÇü ÆÐÅÏ ¸ÅĪ ±â¹ý
¿µ¹®Á¦¸ñ(English Title) Patient Adaptive Pattern Matching Method for Premature Ventricular Contraction(PVC) Classification
ÀúÀÚ(Author) Á¶Àͼº   ±ÇÇõ¼þ   Ik-Sung Cho   Hyeog-Soong Kwon  
¿ø¹®¼ö·Ïó(Citation) VOL 16 NO. 09 PP. 2021 ~ 2030 (2012. 09)
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(Korean Abstract)
Á¶±â½É½Ç¼öÃà(PVC)Àº °¡Àå º¸ÆíÀûÀÎ ºÎÁ¤¸ÆÀ¸·Î ½É½Ç¼¼µ¿, ½É½Çºó¸Æ µî°ú °°Àº À§ÇèÇÑ »óȲÀ» À¯¹ßÇÒ ¼ö ÀÖ´Â °¡´É¼ºÀ» °¡Áö°í Àֱ⠶§¹®¿¡ ÀÌÀÇ Á¶±â °ËÃâÀº ¸Å¿ì Áß¿äÇÏ´Ù. ƯÈ÷ ÀϹÝÀεéÀÇ °Ç°­»óŸ¦ Áö¼ÓÀûÀ¸·Î ¸ð´ÏÅ͸µ ÇØ¾ß ÇÏ´Â ÇコÄÉ¾î ½Ã½ºÅÛ¿¡¼­´Â À̸¦ À§ÇÑ ½ÉÀüµµ ½ÅÈ£ÀÇ ½Ç½Ã°£ 󸮰¡ ÇÊ¿äÇÏ´Ù. Áï, ÃÖ¼ÒÇÑÀÇ ¿¬»ê·®À¸·Î Á¤È®ÇÑ RÆĸ¦ °ËÃâÇÏ°í, ´ë»ó ȯÀÚÀÇ Æ¯Â¡À» ÆľÇÇÏ¿© PVC¸¦ ºÐ·ùÇÒ ¼ö ÀÖ´Â ÀûÇÕÇÑ ¾Ë°í¸®ÁòÀÇ ¼³°è°¡ ÇÊ¿äÇÏ´Ù. µû¶ó¼­ º» ¿¬±¸¿¡¼­´Â PVC ½Ç½Ã°£ ºÐ·ù¸¦ À§ÇÑ È¯ÀÚ ÀûÀÀÇü ÆÐÅÏ ¸ÅĪ ±â¹ýÀ» Á¦¾ÈÇÑ´Ù. À̸¦ À§ÇØ Àü ó¸® °úÁ¤°ú ÀûÀÀ °¡º¯Çü ¹®ÅÎ °ª°ú À©µµ¿ì¸¦ ÅëÇØ RÆĸ¦ °ËÃâÇÏ¿´À¸¸ç, °ËÃâ ´ë»ó¿¡ µû¸¥ Á¤»ó½ÅÈ£ ±ºÀ» ¼±º°ÇÏ°í À̸¦ ¹þ¾î³ª´Â ½ÅÈ£¸¦ ÀÌ»ó½ÅÈ£·Î ºÐ·ùÇϱâ À§ÇØ Çؽ¬ ÇÔ¼ö¸¦ ÅëÇÑ ÆÐÅÏ ¸ÅĪ ±â¹ýÀ» Àû¿ëÇÏ¿´´Ù. Á¦¾ÈÇÑ ¾Ë°í¸®ÁòÀÇ RÆÄ °ËÃâ ¹× Á¤»ó½ÅÈ£ ºÐ·ù ¼º´ÉÀ» Æò°¡Çϱâ À§Çؼ­ MIT-BIH ºÎÁ¤¸Æ µ¥ÀÌÅͺ£À̽º¸¦ »ç¿ëÇÏ¿´´Ù. ¼º´ÉÆò°¡ °á°ú, RÆÄ´Â Æò±Õ 99.33%, ÀÌ»ó½ÅÈ£ ºÐ·ù¿¡ ´ëÇÑ ¿¡·¯À²Àº 0.32%·Î ³ªÅ¸³µ´Ù.
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(English Abstract)
Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons¡¯s physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient¡¯s normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.
Å°¿öµå(Keyword) Á¶±â½É½Ç¼öÃà   RR°£°Ý   ÀûÀÀÇü ¹®Åΰª   À©µµ¿ì   ÆÐÅÏ ¸ÅĪ   MIT-BIH µ¥ÀÌÅͺ£À̽º   Premature Ventricular Contraction(PVC)   RR interval   adaptive threshold   window   pattern matching   MIT-BIH database  
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