Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania.
Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Kaunas, Lithuania.
Sci Rep. 2019 Feb 14;9(1):2006. doi: 10.1038/s41598-019-38638-z.
Physical activity session frequency and distribution over time may play a significant role on survival after major cardiovascular events. However, the existing amount-based metrics do not account for these properties, thus the physical activity pattern is not fully evaluated. The aim of this work is to introduce a metric which accounts for the difference between the actual and uniform distribution of physical activity, thus its value depends on physical activity aggregation over time. The practical application is demonstrated on a step data from 40 participants, half of them diagnosed with chronic cardiovascular disease (CVD). The metric is capable of discriminating among different daily patterns, including going to and from work, walking in a park and being active the entire day. Moreover, the results demonstrate the tendency of CVD patients being associated with higher aggregation values, suggesting that CVD patients spend more time in a sedentary behaviour compared to healthy participants. By combining the aggregation with the intensity metric, such common weekly patterns as inactivity, regular activity and "weekend warrior" can be captured. The metric is expected to have clinical relevance since it may provide additional information on the relationship between physical activity pattern and health outcomes.
身体活动的频次和随时间的分布可能对主要心血管事件后的生存起着重要作用。然而，现有的基于数量的指标并没有考虑到这些性质，因此身体活动模式没有得到充分评估。本工作的目的是引入一种指标，该指标考虑了身体活动实际分布与均匀分布之间的差异，因此其值取决于随时间的身体活动聚集。该指标在 40 名参与者（其中一半被诊断为慢性心血管疾病（CVD））的步数据上进行了实际应用。该指标能够区分不同的日常模式，包括上下班、在公园散步和全天活动。此外，结果表明 CVD 患者的聚集值更高，这表明与健康参与者相比，CVD 患者更倾向于久坐不动。通过将聚集与强度指标相结合，可以捕捉到常见的每周模式，如不活动、规律活动和“周末战士”。该指标有望具有临床相关性，因为它可能提供关于身体活动模式与健康结果之间关系的额外信息。
