Department of Medical Engineering, Graduate School, Kyung Hee University, Seoul 02453, Republic of Korea.
Department of Thoracic and Cardiovascular Surgery, Seoul National University Bundang Hospital, Seongnam-si 13620, Republic of Korea.
Sensors (Basel). 2023 Jun 3;23(11):5308. doi: 10.3390/s23115308.
Electrical impedance tomography (EIT) can monitor the real-time hemodynamic state of a conscious and spontaneously breathing patient noninvasively. However, cardiac volume signal (CVS) extracted from EIT images has a small amplitude and is sensitive to motion artifacts (MAs). This study aimed to develop a new algorithm to reduce MAs from the CVS for more accurate heart rate (HR) and cardiac output (CO) monitoring in patients undergoing hemodialysis based on the source consistency between the electrocardiogram (ECG) and the CVS of heartbeats. Two signals were measured at different locations on the body through independent instruments and electrodes, but the frequency and phase were matched when no MAs occurred. A total of 36 measurements with 113 one-hour sub-datasets were collected from 14 patients. As the number of motions per hour (MI) increased over 30, the proposed algorithm had a correlation of 0.83 and a precision of 1.65 beats per minute (BPM) compared to the conventional statical algorithm of a correlation of 0.56 and a precision of 4.04 BPM. For CO monitoring, the precision and upper limit of the mean ∆CO were 3.41 and 2.82 L per minute (LPM), respectively, compared to 4.05 and 3.82 LPM for the statistical algorithm. The developed algorithm could reduce MAs and improve HR/CO monitoring accuracy and reliability by at least two times, particularly in high-motion environments.
电阻抗断层成像（EIT）可以无创地监测清醒和自主呼吸患者的实时血流动力学状态。然而，从 EIT 图像中提取的心脏容积信号（CVS）幅度较小，容易受到运动伪影（MAs）的影响。本研究旨在开发一种新算法，通过对心跳时心电图（ECG）和 CVS 之间的源一致性进行分析，从 CVS 中减少 MA，从而更准确地监测接受血液透析的患者的心率（HR）和心输出量（CO）。两个信号通过独立的仪器和电极在身体的不同位置进行测量，但在没有 MA 发生时，它们的频率和相位是匹配的。从 14 名患者中总共采集了 36 次测量和 113 个一小时的子数据集。随着每小时运动次数（MI）超过 30，与传统静态算法的相关性为 0.56 和精度为 4.04 BPM 相比，所提出的算法具有 0.83 的相关性和 1.65 BPM 的精度。对于 CO 监测，精度和平均 ∆CO 的上限分别为 3.41 和 2.82 L/min，而统计算法分别为 4.05 和 3.82 L/min。所开发的算法可以减少 MA，将 HR/CO 监测的准确性和可靠性提高至少两倍，特别是在高运动环境中。
