Kunzmann U, von Wagner G, Schöchlin J, Bolz A
FZI Forschungszentrum Informatik Karlsruhe, Germany.
Biomed Tech (Berl). 2002;47 Suppl 1 Pt 2:875-8. doi: 10.1515/bmte.2002.47.s1b.875.
In order for a mobile ECG recorder to be able to classify a heart rhythm online, the significant parameters must be extracted. The relevant parameters are the beginning, peak and end of the QRS-complex, the P- and T-waves, the ST-segment and other significant intervals, such as the RR-interval. The aim of the development was, firstly, stable, real-time-capable QRS detection, which finally achieved values for sensitivity of 98.9% and a positive predictivity of 99.9% on standard ECG databases. Also, a filter-based detection of P- and T-waves was implemented, which can also be performed in real-time on a microcontroller platform.
为了使移动心电图记录仪能够在线对心律进行分类,必须提取重要参数。相关参数包括QRS复合波的起始、峰值和结束、P波和T波、ST段以及其他重要间期,如RR间期。开发的目标首先是实现稳定、具备实时能力的QRS检测,最终在标准心电图数据库上达到了98.9%的灵敏度和99.9%的阳性预测值。此外,还实现了基于滤波器的P波和T波检测,这也可以在微控制器平台上实时进行。