Skoric James, D'Mello Yannick, Aboulezz Ezz, Hakim Siddiqui, Clairmonte Nathan, Lortie Michel, Plant David V
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:2732-2735. doi: 10.1109/EMBC44109.2020.9176245.
Demand of portable health monitoring has been growing due to increasing cardiovascular and respiratory diseases. While both cardiovascular monitoring and respiratory monitoring have been developed independently, there lacks a simple integrated solution to monitor both simultaneously. Seismocardiography (SCG), a method of recording cardiac vibrations with an accelerometer can also be used to extract respiratory information via low frequency chest oscillations. This study used an inertial measurement unit which pairs a 3-axis accelerometer and a 3-axis gyroscope to monitor respiration while maintaining optimum placement protocol for recording SCG. Additionally, the connection between inertial measurement and both respiratory rate and volume were explored based on their correlation with a Spirometer. Respiratory volume was shown to have moderate correlation with chest motion with an average best-case correlation coefficient of 0.679 across acceleration and gyration. The techniques described will assist the design of future SCG algorithms by understanding the sources behind their modulation from respiration. This paper shows that a simplified processing technique can be added to SCG algorithms for respiration monitoring.
由于心血管疾病和呼吸系统疾病的增加，对便携式健康监测的需求一直在增长。虽然心血管监测和呼吸监测是独立发展的，但缺乏一种简单的集成解决方案来同时监测两者。心震图（SCG）是一种用加速度计记录心脏振动的方法，也可用于通过低频胸部振荡提取呼吸信息。本研究使用了一个惯性测量单元，该单元将一个三轴加速度计和一个三轴陀螺仪配对，以监测呼吸，同时保持记录SCG的最佳放置协议。此外，基于惯性测量与肺活量计的相关性，探讨了惯性测量与呼吸频率和呼吸量之间的联系。结果表明，呼吸量与胸部运动具有中等相关性，加速度和旋转的平均最佳相关系数为0.679。通过了解呼吸调制背后的来源，所描述的技术将有助于未来SCG算法的设计。本文表明，可以在SCG算法中添加一种简化的处理技术用于呼吸监测。
