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管理重新连接故障电极后动态脑电阻抗断层成像的错误测量。

Managing erroneous measurements of dynamic brain electrical impedance tomography after reconnection of faulty electrodes.

机构信息

Haoting Li and Xuechao Liu contributed equally to this work.

出版信息

Physiol Meas. 2020 Apr 16;41(3):035002. doi: 10.1088/1361-6579/ab71f4.

DOI:10.1088/1361-6579/ab71f4
PMID:32000152
Abstract

OBJECTIVE

Electrode detachment may occur during dynamic brain electrical impedance tomography (EIT) measurements. After the faulty electrodes have been reset, EIT can restore to steady monitoring but the corrupted data, which will challenge interpretation of the results, are notoriously difficult to recover.

APPROACH

Here, a piecewise processing method (PPM) is introduced to manage the erroneous EIT data after reattachment of faulty electrodes. In the PPM, we define the three phases before, during and after reconnection of the faulty electrode as PI, PII and PIII, respectively. Using this definition, an empirical mode decomposition-based interpolation method is introduced to compensate the corrupted data in PII, using the valid measurements in PI and PIII. Then, the compensated data in PII are spliced at the end of PI. Thus, there will be a surge at the junction of PII and PIII due to the changes in contact state of the repositioned electrodes. Finally, to ensure all the EIT data are obtained under constant electrode settings, we calculate the above changes and eliminate them from the data after PII. To verify the performance of the PPM, experiments based on head models, with anatomical structures and with human subjects were conducted. Metrics including permutation entropy (PE) and image correlation (IC) were proposed to measure the stability of the signal and the quality of the reconstructed EIT images, respectively.

MAIN RESULTS

The results demonstrated that the PE of the processed data was reduced to 0.25 and the IC improved to 0.78.

SIGNIFICANCE

Without iterative calculations the PPM could efficiently manage the erroneous EIT data after reattachment of the faulty electrodes.

摘要

目的

在动态脑电阻抗断层成像(EIT)测量中可能会发生电极脱离。在重置故障电极后,EIT 可以恢复到稳定监测,但已损坏的数据,这将对结果的解释构成挑战,很难恢复。

方法

这里引入了一种分段处理方法(PPM)来管理故障电极重新连接后的错误 EIT 数据。在 PPM 中,我们将故障电极重新连接前、中、后的三个阶段分别定义为 PI、PII 和 PIII。使用此定义,引入了一种基于经验模态分解的插值方法来补偿 PII 中的损坏数据,使用 PI 和 PIII 中的有效测量值。然后,在 PI 的末尾拼接补偿后的 PII 数据。因此,由于重新定位电极的接触状态发生变化,在 PII 和 PIII 的交界处会出现突增。最后,为了确保在恒定电极设置下获得所有 EIT 数据,我们计算上述变化并从 PII 后的数据中消除它们。为了验证 PPM 的性能,我们基于头部模型、具有解剖结构的模型和人体进行了实验。提出了置换熵(PE)和图像相关(IC)等指标来分别测量信号的稳定性和重建的 EIT 图像的质量。

主要结果

结果表明,处理后数据的 PE 降低到 0.25,IC 提高到 0.78。

意义

无需迭代计算,PPM 可以有效地管理故障电极重新连接后的错误 EIT 数据。

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