Brown Stephen B R E, Brosschot Jos F, Versluis Anke, Thayer Julian F, Verkuil Bart
Department of Health, Medical, and Neuropsychology, Leiden University, Leiden, Netherlands.
Leiden Institute for Brain and Cognition, Leiden, Netherlands.
Front Neurosci. 2020 Oct 22;14:564123. doi: 10.3389/fnins.2020.564123. eCollection 2020.
Frequent or chronic reduction in heart rate variability (HRV) is a powerful predictor of cardiovascular disease, and psychological stress has been suggested to be a co-determinant of this reduction. Recently, we evaluated various methods to measure additional HRV reduction in everyday life and to relate these reductions to psychological stress. In the current paper, we thoroughly evaluate these methods and add two new methods in both newly acquired and reanalyzed datasets. All of these methods use a subset of 24 h worth of HRV and movement data to do so: either the first 10 min of every hour, the full 24 h, a combination of 10 min from three consecutive hours, a classification of level of movement, the data from day to detect episodes in day + 1, or a range of activities during lab calibration. The method that used the full 24 h worth of data detected the largest percentage of episodes of reduced additional HRV that matched with self-reported stress levels, making this method the most promising, while using the first 10 min from three consecutive hours was a good runner-up.
心率变异性(HRV)的频繁或慢性降低是心血管疾病的有力预测指标,并且心理压力被认为是这种降低的一个共同决定因素。最近,我们评估了各种方法,以测量日常生活中额外的HRV降低情况,并将这些降低与心理压力联系起来。在本文中,我们全面评估了这些方法,并在新获取和重新分析的数据集中添加了两种新方法。所有这些方法都使用了相当于24小时的HRV和运动数据的一个子集来进行操作:每小时的前10分钟、完整的24小时、连续三个小时中各10分钟的组合、运动水平分类、来自第1天的数据以检测第2天的发作情况,或者实验室校准期间的一系列活动。使用完整24小时数据的方法检测到与自我报告的压力水平相匹配的额外HRV降低发作的百分比最大,使该方法最具前景,而使用连续三个小时的前10分钟则是第二好的方法。