Department of Psychology I, University of Würzburg, Marcusstr. 9-11, 97070, Würzburg, Germany.
Behav Res Methods. 2011 Dec;43(4):1161-70. doi: 10.3758/s13428-011-0107-7.
The importance of appropriate handling of artifacts in interbeat interval (IBI) data must not be underestimated. Even a single artifact may cause unreliable heart rate variability (HRV) results. Thus, a robust artifact detection algorithm and the option for manual intervention by the researcher form key components for confident HRV analysis. Here, we present ARTiiFACT, a software tool for processing electrocardiogram and IBI data. Both automated and manual artifact detection and correction are available in a graphical user interface. In addition, ARTiiFACT includes time- and frequency-based HRV analyses and descriptive statistics, thus offering the basic tools for HRV analysis. Notably, all program steps can be executed separately and allow for data export, thus offering high flexibility and interoperability with a whole range of applications.
在心跳间隔 (IBI) 数据中,适当处理伪影的重要性不容低估。即使单个伪影也可能导致不可靠的心率变异性 (HRV) 结果。因此,稳健的伪影检测算法和研究人员手动干预的选项是进行可靠 HRV 分析的关键组成部分。在这里,我们介绍了用于处理心电图和 IBI 数据的软件工具 ARTiiFACT。在图形用户界面中,既可以进行自动也可以进行手动的伪影检测和校正。此外,ARTiiFACT 还包括基于时间和频率的 HRV 分析和描述性统计,因此提供了 HRV 分析的基本工具。值得注意的是,所有程序步骤都可以单独执行,并允许数据导出,从而提供了与各种应用程序的高度灵活性和互操作性。