An open source benchmarked toolbox for cardiovascular waveform and interval analysis.
An open source benchmarked toolbox for cardiovascular waveform and interval analysis.
复制标题
DOI：
10.1088/1361-6579/aae021
复制
发表时间：
2018-10-11
影响因子：
3.2
通讯作者：
Clifford GD
中科院分区：
文献类型：
--
作者：
Vest AN;Da Poian G;Li Q;Liu C;Nemati S;Shah AJ;Clifford GD
变异性指标有望成为自主神经功能、不良心血管结局预测、心理生理状态和总体健康状况的潜在指标。尽管心率变异性 (HRV) 的研究已经流行了几十年，但用于预处理、加窗和选择适当参数的方法在学术和临床研究人员中缺乏共识。此外，出版物中省略了许多重要步骤，从而妨碍了重现性。为了解决这个问题，我们编译了一个全面的开源模块化工具箱，用于计算原始心血管时间序列和 RR 间隔的 HRV 指标和其他相关变异指数。该软件被称为 PhysioNet 心血管信号工具箱，采用 MATLAB 编程语言实现，具有标准（开放）输入和输出格式，不需要外部库。我们的软件的功能与其他广泛使用和引用的 HRV 工具箱进行比较，以确定重要的差异。我们的研究结果表明，HRV 分析方法的微小差异可能会导致不同的结果，这一因素可能导致研究缺乏可重复性和 HRV 指标的临床适用性。现有的 HRV 工具箱不包括标准化预处理、信号质量指数（用于噪声片段去除）和异常节律检测，因此在存在中度至高噪声或心律失常的情况下可能会导致重大错误。因此，我们描述了包含经过验证的工具来解决这些问题。我们还对默认值和测试/报告提出建议。
Variability metrics hold promise as potential indicators for autonomic function, prediction of adverse cardiovascular outcomes, psychophysiological status, and general wellness. Although the investigation of heart rate variability (HRV) has been prevalent for several decades, the methods used for preprocessing, windowing, and choosing appropriate parameters lacks consensus among academic and clinical investigators. Moreover, many of the important steps are omitted from publications, preventing reproducibility. To address this, we have compiled a comprehensive and open-source modular toolbox for calculating HRV metrics and other related variability indices, on both raw cardiovascular time series, and RR intervals. The software, known as the PhysioNet Cardiovascular Signal Toolbox, is implemented in the MATLAB programming language, with standard (open) input and output formats, and requires no external libraries. The functioning of our software is compared with other widely used and referenced HRV toolboxes to identify important differences. Our findings demonstrate how modest differences in the approach to HRV analysis can lead to divergent results, a factor that might have contributed to the lack of repeatability of studies and clinical applicability of HRV metrics. Existing HRV toolboxes do not include standardized preprocessing, signal quality indices (for noisy segment removal), and abnormal rhythm detection and are therefore likely to lead to significant errors in the presence of moderate to high noise or arrhythmias. We therefore describe the inclusion of validated tools to address these issues. We also make recommendations for default values and testing/reporting.
登录
查看更多内容
DOI：
10.1016/s0735-1097(00)00595-7
发表时间：
2000-05-01
影响因子：
24
作者：
Bernardi, L;Wdowczyk-Szulc, J;Sleight, P
通讯作者：
Sleight, P
影响因子：
9.6
作者：
Cooper, AB;Thornley, KS;Hanly, PJ
通讯作者：
Hanly, PJ
影响因子：
1.9
作者：
Berkowitsch, A;Zareba, W;Pitschner, HF
通讯作者：
Pitschner, HF
DOI：
10.1016/j.physa.2005.08.080
发表时间：
2006-05-15
影响因子：
3.3
作者：
Bauer, A;Kantelhardt, JW;Schmidt, G
通讯作者：
Schmidt, G
影响因子：
1.3
作者：
Bauer, A;Schmidt, G
通讯作者：
Schmidt, G