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基于表面肌电图的吸气努力模型估计

Model-Based Estimation of Inspiratory Effort Using Surface EMG.

作者信息

Grashoff Jan, Petersen Eike, Walterspacher Stephan, Rostalski Philipp

出版信息

IEEE Trans Biomed Eng. 2023 Jan;70(1):247-258. doi: 10.1109/TBME.2022.3188183. Epub 2022 Dec 26.

DOI:10.1109/TBME.2022.3188183
PMID:35786547
Abstract

OBJECTIVE

The quantification of inspiratory patient effort in assisted mechanical ventilation is essential for the adjustment of ventilatory assistance and for assessing patient-ventilator interaction. The inspiratory effort is usually measured via the respiratory muscle pressure (P ) derived from esophageal pressure (P ) measurements. As yet, no reliable non-invasive and unobtrusive alternatives exist to continuously quantify P .

METHODS

We propose a model-based approach to estimate P non-invasively during assisted ventilation using surface electromyographic (sEMG) measurements. The method combines the sEMG and ventilator signals to determine the lung elastance and resistance as well as the neuromechanical coupling of the respiratory muscles via a novel regression technique. Using the equation of motion, an estimate for P can then be calculated directly from the lung mechanical parameters and the pneumatic ventilator signals.

RESULTS

The method was applied to data recorded from a total of 43 ventilated patients and validated against P -derived P . Patient effort was quantified via the P pressure-time-product (PTP). The sEMG-derived PTP estimated using the proposed method was highly correlated to P -derived PTP ([Formula: see text]), and the breath-wise deviation between the two quantities was [Formula: see text].

CONCLUSION

The estimated, sEMG-derived P is closely related to the P -based reference and allows to reliably quantify inspiratory effort.

SIGNIFICANCE

The proposed technique provides a valuable tool for physicians to assess patients undergoing assisted mechanical ventilation and, thus, may support clinical decision making.

摘要

目的

在辅助机械通气中对患者吸气努力进行量化,对于调整通气辅助以及评估患者 - 呼吸机相互作用至关重要。吸气努力通常通过源自食管压力(P)测量的呼吸肌压力(P)来衡量。目前,尚无可靠的非侵入性且不引人注意的替代方法来持续量化P。

方法

我们提出一种基于模型的方法,在辅助通气期间使用表面肌电图(sEMG)测量来无创估计P。该方法通过一种新颖的回归技术,将sEMG和呼吸机信号相结合,以确定肺弹性和阻力以及呼吸肌的神经机械耦合。然后,使用运动方程,可以直接从肺力学参数和气动呼吸机信号计算出P的估计值。

结果

该方法应用于总共43例通气患者记录的数据,并与源自P的P进行验证。通过P压力 - 时间乘积(PTP)对患者努力进行量化。使用所提出方法估计的源自sEMG的PTP与源自P的PTP高度相关([公式:见原文]),并且这两个量之间的逐次呼吸偏差为[公式:见原文]。

结论

估计的、源自sEMG的P与基于P的参考值密切相关,并能够可靠地量化吸气努力。

意义

所提出的技术为医生评估接受辅助机械通气的患者提供了一种有价值的工具,因此可能支持临床决策。

相似文献

1
Model-Based Estimation of Inspiratory Effort Using Surface EMG.基于表面肌电图的吸气努力模型估计
IEEE Trans Biomed Eng. 2023 Jan;70(1):247-258. doi: 10.1109/TBME.2022.3188183. Epub 2022 Dec 26.
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Surface EMG-based quantification of inspiratory effort: a quantitative comparison with P.基于表面肌电图的吸气努力定量:与 P 的定量比较。
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Real-time computation of a patient's respiratory effort during ventilation.通气期间患者呼吸努力的实时计算。
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Automated characterization of patient-ventilator interaction using surface electromyography.使用表面肌电图对患者-呼吸机相互作用进行自动特征分析。
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Estimation of inspiratory muscle pressure in critically ill patients.危重症患者吸气肌压力的评估。
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Estimation of patient's inspiratory effort from the electrical activity of the diaphragm.从膈肌的电活动估算患者的吸气努力。
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Severe diaphragmatic dysfunction with preserved activity of accessory respiratory muscles in a critically ill child: a case report of failure of neurally adjusted ventilatory assist (NAVA) and successful support with pressure support ventilation (PSV).严重膈肌功能障碍伴辅助呼吸肌活动正常的危重症患儿:神经调节辅助通气(NAVA)失败和压力支持通气(PSV)成功支持的病例报告。
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Inspiratory capacity at inflation hold in ventilated newborns: a surrogate measure for static compliance of the respiratory system.在通气新生儿中进行吸气保持时的吸气量:呼吸系统静态顺应性的替代测量指标。
Pediatr Crit Care Med. 2012 Sep;13(5):560-7. doi: 10.1097/PCC.0b013e31823c99f5.

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