论文部分内容阅读
基于心血管疾病患者的心率变异性(HRV)、心率减速力(DC)以及脉搏波传导速度(PWV)等多变量的测量与分析,研究心肌梗死风险早期评估的可行性。随机选择35名心血管疾病患者(11例心肌梗死、8例冠心病、6例动脉硬化和10例高血压)和31名健康常对照,采用自主研制的心肌梗死风险评估平台,采集15min的心电数据和1min的脉搏波数据,进行HRV、DC和PWV分析,并与对照组结果进行比较;实验结果表明心血管疾病组与对照组的HRV、DC和PWV分析结果具有明显的差异性,而其中DC和HRV时域分析方法中的NN50、PNN50及TINN还能有效反映出相关病理的渐变过程。综合HRV、DC和PWV等参变量的趋势分析能够为心肌梗死早期风险评估、临床筛查和预警提供参考。
Based on multivariate measurement and analysis of heart rate variability (HRV), heart rate deceleration (DC) and pulse wave velocity (PWV) in patients with cardiovascular diseases, the feasibility of early assessment of myocardial infarction risk was studied. Thirty-five patients with cardiovascular disease (11 myocardial infarction, 8 coronary heart disease, 6 arteriosclerosis and 10 hypertension) and 31 healthy controls were randomly selected. The risk assessment platform of myocardial infarction Electrical data and pulse wave data of 1min, HRV, DC and PWV were analyzed and compared with the control group results; the experimental results show that the results of HRV, DC and PWV in cardiovascular disease group and control group have obvious differences, Among them, NN50, PNN50 and TINN in the time domain analysis method of DC and HRV can effectively reflect the gradual change of related pathology. The trend analysis of parameters such as HRV, DC and PWV can provide reference for early risk assessment, clinical screening and early warning of myocardial infarction.