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一种用于检测咬合面非龋洞性龋病的分数电阻抗模型。

A fractional electrical impedance model in detection of occlusal non-cavitated carious.

作者信息

Morais Andrea P, Pino Alexandre V, Souza Marcio N

机构信息

Biomedical Engineering Program - COPPE at Federal University of Rio de Janeiro, Centro de Tecnologia, Bloco H, sala 327, Brazil, P.O. Box 68510, Postal Code 21945-970.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:6551-4. doi: 10.1109/IEMBS.2010.5627098.

DOI:10.1109/IEMBS.2010.5627098
PMID:21096504
Abstract

Identification of occlusal caries remains a major concern for the diagnosis, which is still highly subjective and presents a considerable variability among clinicians. Dentists have been observed an increase of a specifically type of caries lesion, the hidden caries. Among the available techniques to assess the hidden caries, the measurement of electrical impedance has been shown to be one of the most promising. This paper presents a fractional electrical model for the tooth and uses such a model associated to a BioImpedance Spectroscopy (BIS) method based on the current response to a step voltage excitation. An analytical solution for the current response is presented based on a fractional calculus approach. Estimate parameters of the proposed model achieved using an in vitro data acquired in a protocol performed to collect bioimpedance data showed that it seems possible to detect occlusal non-cavitated caries, and that the principal confounding factor in the diagnosis of the incipient occlusal caries, the pigmented areas, can also be differentiated.

摘要

咬合面龋的识别仍然是诊断中的一个主要问题,其诊断仍然高度主观,并且在临床医生之间存在相当大的差异。已经观察到牙医中一种特定类型的龋损,即隐匿性龋的发生率有所增加。在评估隐匿性龋的现有技术中,电阻抗测量已被证明是最有前景的技术之一。本文提出了一种牙齿的分数阶电学模型,并将该模型与基于阶跃电压激励下的电流响应的生物阻抗谱(BIS)方法相关联。基于分数阶微积分方法给出了电流响应的解析解。使用在收集生物阻抗数据的实验方案中获取的体外数据对所提出模型的参数进行估计,结果表明似乎可以检测到咬合面非龋洞性龋,并且在早期咬合面龋诊断中主要的混杂因素,即色素沉着区域,也能够被区分。

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A fractional electrical impedance model in detection of occlusal non-cavitated carious.一种用于检测咬合面非龋洞性龋病的分数电阻抗模型。
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:6551-4. doi: 10.1109/IEMBS.2010.5627098.
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