Real-time management of faulty electrodes in electrical impedance tomography.

IEEE transactions on bio-medical engineering(2009)

引用 27|浏览5
暂无评分
摘要
Completely or partially disconnected electrodes are a fairly common occurrence in many electrical impedance tomography (EIT) clinical applications. Several factors can contribute to electrode disconnection: patient movement, perspiration, manipulations by clinical staff, and defective electrode leads or electronics. By corrupting several measurements, faulty electrodes introduce significant image artifacts. In order to properly manage faulty electrodes, it is necessary to: 1) account for invalid data in image reconstruction algorithms and 2) automatically detect faulty electrodes. This paper presents a two-part approach for real-time management of faulty electrodes based on the principle of voltage-current reciprocity. The first part allows accounting for faulty electrodes in EIT image reconstruction without a priori knowledge of which electrodes are at fault. The method properly weights each measurement according to its compliance with the principle of voltage-current reciprocity. Results show that the algorithm is able to automatically determine the valid portion of the data and use it to calculate high-quality images. The second part of the approach allows automatic real-time detection of at least one faulty electrode with 100% sensitivity and two faulty electrodes with 80% sensitivity enabling the clinical staff to fix the problem as soon as possible to minimize data loss.
更多
查看译文
关键词
image artifacts,automatic real-time detection,tomography,voltage--current reciprocity principle,faulty electrodes,real-time management,biomedical electrodes,image reconstruction,electrode disconnection,voltage-current reciprocity,partially disconnected electrodes,bioelectric phenomena,biomedical instrumentation,image reconstruction algorithms,electrical impedance tomography (eit),electrical impedance tomography,patient movement,data loss,electric impedance imaging,medical image processing,defective electrode leads,perspiration
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要