层状体结构物性参数化成等效电路模型。

Jiho Lee, Sung-Min Park
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引用次数: 2

摘要

背景:本研究提出了一种新的技术,通过参数化电学和几何特性来建立等效电路模型(ECM),用于分析分层体结构对经皮神经电刺激(TENS)的响应。由于难以将物理性质的个人变异性投射到ECM中,许多经典的ECM是非参数的。然而,不考虑患者自身的可变性影响了患者对TENS的身体反应分析和TENS参数设计的个人优化。为了克服这一限制,我们提出了一种基于组织属性(TPB)的方法,用于直接参数化分层身体结构中的物理属性,从而能够量化个人变异的影响。结果:首先通过体外模体研究验证了所提出的方法,然后将其应用于前臂上的TENS的体内分析。TPB-ECM计算前臂的阻抗网络和相应的TENS反应。此外,模拟的阻抗与已知的经验阻抗特性很好地吻合。结论:与非参数化的传统ecm相比,TPB方法使用了参数化的电路元件,从而克服了传统ecm的个人变异性问题。因此,TPB-ECM具有广泛应用于TENS分析的潜力,可以为TENS参数设计提供有影响力的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Parameterization of physical properties of layered body structure into equivalent circuit model.

Background: This study presents a novel technique to develop an equivalent circuit model (ECM) for analyzing the responses of the layered body structure to transcutaneous electrical nerve stimulation (TENS) by parameterizing electrical and geometrical properties.Many classical ECMs are non-parametric because of the difficulty in projecting intrapersonal variability in the physical properties into ECM. However, not considering the intrapersonal variability hampers patient-specifically analyzing the body response to TENS and personal optimization of TENS parameter design. To overcome this limitation, we propose a tissue property-based (TPB) approach for the direct parameterization of the physical properties in the layered body structure and thus enable to quantify the effects of intrapersonal variability.

Results: The proposed method was first validated through in vitro phantom studies and then was applied in-vivo to analyze the TENS on the forearm. The TPB-ECM calculated the impedance network in the forearm and corresponding responses to TENS. In addition, the modelled impedance was in good agreement with well-known impedance properties that have been achieved empirically.

Conclusions: The TPB approach uses the parameterized circuit components compared to non-parametric conventional ECMs, thus overcoming the intrapersonal variability problem of the conventional ECMs. Therefore, the TPB-ECM has a potential for widely-applicable TENS analysis and could provide impactful guidance in the TENS parameter design.

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