中国组织工程研究
中國組織工程研究
중국조직공정연구
Journal of Clinical Rehabilitative Tissue Engineering Research
2013年
4期
653-657
,共5页
刘新旭%苏智剑%高振奎%刘延涛%夏振宏%刘娜
劉新旭%囌智劍%高振奎%劉延濤%夏振宏%劉娜
류신욱%소지검%고진규%류연도%하진굉%류나
骨关节植入物%骨与关节图像与影像%心电信号%ST 段%信号处理%二维云模型%聚类分析%CSE 数据库%数字化医学%其他基金%骨关节植入物图片文章
骨關節植入物%骨與關節圖像與影像%心電信號%ST 段%信號處理%二維雲模型%聚類分析%CSE 數據庫%數字化醫學%其他基金%骨關節植入物圖片文章
골관절식입물%골여관절도상여영상%심전신호%ST 단%신호처리%이유운모형%취류분석%CSE 수거고%수자화의학%기타기금%골관절식입물도편문장
背景:目前对于异常 ST 段的形态特征的评价体系,尚无精确数学化模型分类及识别标准,这阻碍了对某些心血管疾病进行计算机自动识别程序算法的进展.目的:找到一种符合医学诊断逻辑思维的心电信号 ST 段分析方法,为心电图 ST 段变化的实时分析提供新的思路.方法:针对采集的心电数据模糊性和随机性较大的特点,提出了一种基于两维云模型的心电信号 ST 段的检测方法,其对二维正态云发生器隶属度进行判断,并进行心电信号 ST 段的形态判定.结果与结论:利用 Matlab 对本算法进行仿真,并通过标准心电数据库(欧共体 CSE 数据库)中数据进行算法准确性验证,统计结果表明该算法 ST 段的识别率较高,对于大数据量的心电信号处理快捷有效,为 ST 段的准确分析提供了新的方法.
揹景:目前對于異常 ST 段的形態特徵的評價體繫,尚無精確數學化模型分類及識彆標準,這阻礙瞭對某些心血管疾病進行計算機自動識彆程序算法的進展.目的:找到一種符閤醫學診斷邏輯思維的心電信號 ST 段分析方法,為心電圖 ST 段變化的實時分析提供新的思路.方法:針對採集的心電數據模糊性和隨機性較大的特點,提齣瞭一種基于兩維雲模型的心電信號 ST 段的檢測方法,其對二維正態雲髮生器隸屬度進行判斷,併進行心電信號 ST 段的形態判定.結果與結論:利用 Matlab 對本算法進行倣真,併通過標準心電數據庫(歐共體 CSE 數據庫)中數據進行算法準確性驗證,統計結果錶明該算法 ST 段的識彆率較高,對于大數據量的心電信號處理快捷有效,為 ST 段的準確分析提供瞭新的方法.
배경:목전대우이상 ST 단적형태특정적평개체계,상무정학수학화모형분류급식별표준,저조애료대모사심혈관질병진행계산궤자동식별정서산법적진전.목적:조도일충부합의학진단라집사유적심전신호 ST 단분석방법,위심전도 ST 단변화적실시분석제공신적사로.방법:침대채집적심전수거모호성화수궤성교대적특점,제출료일충기우량유운모형적심전신호 ST 단적검측방법,기대이유정태운발생기대속도진행판단,병진행심전신호 ST 단적형태판정.결과여결론:이용 Matlab 대본산법진행방진,병통과표준심전수거고(구공체 CSE 수거고)중수거진행산법준학성험증,통계결과표명해산법 ST 단적식별솔교고,대우대수거량적심전신호처리쾌첩유효,위 ST 단적준학분석제공료신적방법.
@@@@BACKGROUND: There is no precise classificated mathematical model and identification standard for the morphological characteristics of abnormal ST segment, and therefore, the improvement of automatical recognization wil be limited in some cardiovascular diseases diagnoses. OBJECTIVE: To find a new method meeting the medical diagnosis logical thinking for analyzing the ST segment in electrocardiogram signal, and to provide new ideas for real-time analysis of the changes of electrocardiogram of ST segment. METHODS: A new algorithm for detecting ST segment in electrocardiogram signal based on two-dimensional cloudy model theory was proposed in view of the fuzziness and randomness of electrocardiogram signal. And then, it estimated the membership grade of two-dimensional cloud generator and identified the morphology of ST segment in electrocardiogram. RESULTS AND DISCUSSION: The algorithm was simulated with Matlab, and the algorithm accuracy was verified by standard ECG database (European Community CSE database). The statistical results showed that the algorithm had a high identification rate of ST segment, and it was shortcut and effective for processing the large amount of data which provide a new method for the accurate analysis of the ST segment.