介绍ECG-101G型数字单通道式心电图机的工作原理,探讨心电图机的常见故障维修案例。方法:简要介绍心电图机的工作原理,分析其故障现象,选择合理的故障测试点完成故障排除。结果:通过分析心电图机常见故障案例,提出了相应的解决办法,提炼了分析思路。结论:通过对心电图机案例分析、维修操作,能够锻炼和提高临床工程师排除故障的能力,确保心电图机的安全使用。

Objective:To take ECG-101G digital electrocardiograph (ECG) with a single channel for example, this paper aims to introduce its basic principle and discuss three examples of common troubleshooting for breakdowns. Methods: At first, this paper introduces basic principles of ECG. With analyzing the fault phenomenon, this paper chooses proper testing points and finishes the troubleshooting for breakdowns. Results:With the analysis of three examples of common breakdowns, this paper proposes corresponding solution and refines the analysis mentality. Conclusion:Good understanding of basic principle and troubleshooting for breakdowns is helpful for clinical engineers to practice the ability of maintaining and learn more about ECG.

分析影响数字心电图机检定结果的主要因素,采取相应的解决措施,确保使用安全。方法:对数字心电图机检定中的每个步骤进行分析,寻找合理的解决方案,并通过实践验证。结果:在实际检定工作中,验证了各项解决方案的可行性,确保了数字心电图机的质量安全。结论:数字心电图机的检定是医学计量的重要组成部分,通过定期检定,确保了临床诊断的准确性。

Objective:To analyze the test results of several major factors, and take corresponding measures to ensure the safe use of the digital ECG machine. Methods:To analyze the each step of digital ECG machine’s verification, summarized the influence factors of the testing results, to find a reasonable solutions, and through practice to verify. Results:In the actual verification work, verified the feasibility of the solutions, to ensure the quality and safety of digital ECG machine;Conclusion:digital ECG verification is an important part of medical metrology, through regular verification to ensure the accuracy of medical diagnosis.

本文针对心电图机检定过程，依据心电图机的检定规程，列举出现的问题，并对问题进行初步分析，从而得出消除问题的解决方法，以保证之后的检定数据准确可靠。

The paper lists the problems through calibration processing of ECG, on the basis of verification reg-ulation of ECG. The paper analyzes the problems and puts forward solution ensuring the accuracy and reliability of test data.

对急性脑出血患者的心电图检查情况进行临床分析,从而探讨急性脑出血与心电图改变的关系。方法:选取2011年4月至2012年10月我院住院部收治的急性脑出血患者102例,患者入院前以及治疗后采用十二导心电图机进行心电图检查,对心电图检查结果进行统计分析,并注意观察心电图变化特点与脑出血之间的关系。结果:102例急性脑出血患者经心电图检查,结果显示心电图改变主要表现为ST-T改变或心律失常,其中心电图检测异常患者中脑出血部位主要为脑叶、壳核、丘脑以及蛛网膜下腔、小脑等。结论:急性脑出血患者心电图变化与出血部位以及患者的病情有关,其中急性脑出血主要集中于中、重症患者。

Objective:To explore relationship between acute cerebral hemorrhage and ECG changes by clinical analysis of ECG examination for patients with acute cerebral hemorrhage .Method:102 cases of in-patients with acute cerebral hemorrhage of our hospital from Apr .2011 to Oct.2012 were selected ,adopted 12-lead ECG machine for ECG exmanination before and after treatment ,then recorded and analyzed the re-sults of examination ,relationship between ECG change features and cerebral hemorrhages was observed .Re-sult:It showed that the main ECG changes were ST-T changes or arrhythmias through ECG examination for 102 patients with acute cerebral hemorrhage ,of which the main cerebral hemorrhage sites were lobe , put a-men, thalamus , subarachnoid space , cerebellum and so on .Conclusion:ECG changes of patients with acute cerebral hemorrhage has relationship with bleeding site and the patient''s condition , and acute cerebral hem-orrhage is mainly focused on moderate and severe patients .

为了提高心电图(ECG)信号的身份识别正确率,提出一种小波变换和支持向量机相融合的ECG身份识别方法 (IWT-ABC-SVM)。采用一种小波阈值函数对ECG进行去噪处理,提取ECG特征,将ECG特征输入到支持向量机中进行学习,采用人工蜂群算法优化支持向量机参数,建立ECG的身份识别模型,采用MIT-BIH心电图数据进行仿真测试。仿真结果表明,相对于其他识别方法,IWT-ABC-SVM提高了ECG身份识别的正确率和可靠性。

In order to improve the rate of human identification based on ECG, a novel ECG human identification approach (IWT-ABC-SVM)is proposed based on wavelet analysis and Support Vector Machine. Wavelet threshold function is used to de-noise the ECG, and the ECG features are extracted;the ECG features are input to Support Vector Machine to learn, and the pa-rameters of Support Vector Machine are optimized by artificial bee colony algorithm;the human identification classifier is estab-lished and the simulation experiment is carried out by using MIT-BIH ECG data. The results show that compared with other identification methods, the proposed method has improved the identification accuracy and reliability.