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自动微伏 T 波交替识别与预处理后仍存在的心电图干扰有关。

Automatic microvolt T-wave alternans identification in relation to ECG interferences surviving preprocessing.

机构信息

Department of Biomedical, Electronics and Telecommunication Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy.

出版信息

Med Eng Phys. 2011 Jan;33(1):17-30. doi: 10.1016/j.medengphy.2010.08.014.

DOI:10.1016/j.medengphy.2010.08.014
PMID:20920875
Abstract

The aim was to investigate the effect of interferences surviving preprocessing (residual noise, baseline wanderings, respiration modulation, replaced beats, missed beats and T-waves misalignment) on automatic identification of T-wave alternans (TWA), an ECG index of risk for sudden cardiac death. The procedures denominated fast-Fourier-transform spectral method (FFTSM), complex-demodulation method (CDM), modified-moving-average method (MMAM), Laplacian-likelihood-ratio method (LLRM), and adaptive-match-filter method (AMFM) were applied to interferences-corrupted synthetic ECG tracings and Holter ECG recordings from control-healthy subjects (CH-group; n=25) and acute-myocardial-infarction patients (AMI group; n=25). The presence of interferences in simulated data caused detection of false-positive TWA by all techniques but the FFTSM and AMFM. Clinical applications evidenced a discrepancy in that the FFTSM and LLRM detected no more than one TWA case in each population, whereas the CDM, MMAM, and AMFM detected TWA in all CH-subjects and AMI-patients, with significantly lower TWA amplitude in the former group. Because the AMFM is not prone to false-positive TWA detections, the latter finding suggests TWA as a phenomenon having continuously changing amplitude from physiological to pathological conditions. Only occasional detection of TWA by the FFTSM and LLRM in clinics can be ascribed to their limited ability in identifying TWA in the presence of interferences surviving preprocessing.

摘要

目的是研究预处理后残留干扰(残余噪声、基线漂移、呼吸调制、替换搏动、漏搏和 T 波错位)对 T 波交替(TWA)自动识别的影响,TWA 是一种心电图心源性猝死风险指数。Fast-Fourier-Transform 谱方法(FFTSM)、复解调方法(CDM)、修正移动平均方法(MMAM)、拉普拉斯似然比方法(LLRM)和自适应匹配滤波方法(AMFM)等方法被应用于干扰污染的合成心电图描记和来自对照健康受试者(CH 组;n=25)和急性心肌梗死患者(AMI 组;n=25)的动态心电图记录。在模拟数据中存在干扰的情况下,所有技术都检测到了假阳性 TWA,但 FFTSM 和 AMFM 除外。临床应用存在差异,FFTSM 和 LLRM 在每个群体中仅检测到一个 TWA 病例,而 CDM、MMAM 和 AMFM 在所有 CH 受试者和 AMI 患者中均检测到 TWA,前者的 TWA 振幅明显较低。由于 AMFM 不易出现假阳性 TWA 检测,因此后一种发现表明 TWA 是一种振幅从生理到病理条件不断变化的现象。FFTSM 和 LLRM 在临床上偶尔检测到 TWA 可归因于它们在预处理后残留干扰存在的情况下识别 TWA 的能力有限。

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