利用光学技术分析心肌梗死信号。

Analysis of myocardial infarction signals using optical technique.

作者信息

Mahri Nurhafizah, Gan Kok Beng, Mohd Ali Mohd Alauddin, Jaafar Mohd Hasni, Meswari Rusna

机构信息

a Jabatan Kejuruteraan Elektrik, Elektronik dan Sistem, Fakulti Kejuruteraan Alam Bina , Universiti Kebangsaan Malaysia , Bangi , Selangor , Malaysia ;

b Jabatan Elektronik, Fakulti Kejuruteraan Elektrik dan Elektronik , Universiti Tun Hussein Onn Malaysia , Batu Pahat , Johor , Malaysia ;

出版信息

J Med Eng Technol. 2016;40(4):155-61. doi: 10.3109/03091902.2016.1153740. Epub 2016 Mar 24.

DOI:10.3109/03091902.2016.1153740

PMID:27010162

Abstract

The risk of heart attack or myocardial infarction (MI) may lead to serious consequences in mortality and morbidity. Current MI management in the triage includes non-invasive heart monitoring using an electrocardiogram (ECG) and the cardic biomarker test. This study is designed to explore the potential of photoplethysmography (PPG) as a simple non-invasive device as an alternative method to screen the MI subjects. This study emphasises the usage of second derivative photoplethysmography (SDPPG) intervals as the extracted features to classify the MI subjects. The statistical analysis shows the potential of "a-c" interval and the corrected "a-cC" interval to classify the subject. The sensitivity of the predicted model using "a-c" and "a-cC" is 90.6% and 81.2% and the specificity is 87.5% and 84.4%, respectively.

摘要

心脏病发作或心肌梗死（MI）的风险可能会导致死亡率和发病率方面的严重后果。当前在分诊中对心肌梗死的管理包括使用心电图（ECG）进行非侵入性心脏监测以及心脏生物标志物检测。本研究旨在探索光电容积脉搏波描记法（PPG）作为一种简单的非侵入性设备作为筛查心肌梗死患者的替代方法的潜力。本研究强调使用二阶导数光电容积脉搏波描记法（SDPPG）间期作为提取的特征来对心肌梗死患者进行分类。统计分析显示了“a - c”间期和校正后的“a - cC”间期对分类患者的潜力。使用“a - c”和“a - cC”的预测模型的敏感性分别为90.6%和81.2%，特异性分别为87.5%和84.4%。