Performance Evaluation of Five Types of Ag/AgCl Bio-Electrodes for Cerebral Electrical Impedance Tomography

Electrical impedance tomography (EIT) is an emerging medical imaging technique, which has already been investigated in several clinical applications due to its low-cost, non-invasiveness, non-radioactivity, high temporal resolution, and great sensitivity to impedance changes. One potential use of EI...

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Veröffentlicht in:Annals of biomedical engineering 2011-07, Vol.39 (7), p.2059-2067
Hauptverfasser: Xu, Shiwei, Dai, Meng, Xu, Canhua, Chen, Chaoshuang, Tang, Mengxing, Shi, Xuetao, Dong, Xiuzhen
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Sprache:eng
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Zusammenfassung:Electrical impedance tomography (EIT) is an emerging medical imaging technique, which has already been investigated in several clinical applications due to its low-cost, non-invasiveness, non-radioactivity, high temporal resolution, and great sensitivity to impedance changes. One potential use of EIT is to perform long-term continuous imaging monitoring of brain for patients who suffer from severe cerebral diseases. However, this application requires a demanding performance of electrodes because of the characteristics of cerebral EIT measurements. Although Ag/AgCl bio-electrodes are widely used for clinical practices or EIT research at the moment, influences of different types of Ag/AgCl electrodes on cerebral EIT measurements have not been investigated. In this study, five common types of Ag/AgCl bio-electrodes were put into comparison by measuring the forearm and the brain of 10 healthy adult volunteers and evaluating those data in frequency or time domain in terms of contact impedance, uniformity, signal-to-noise ratio, and stability. Results show that Ag/AgCl powder electrode has an overall best performance with as low contact impedance as commercial ECG electrodes ( p  > 0.05), high SNR (60.3 ± 4.5 dB), better uniformity (coefficient of correlation 0.95 ± 0.03), and greater stability (slope 0.68 ± 0.03). After further improvement in design and instrumentation, Ag/AgCl powder electrode is likely to become the optimal choice for cerebral EIT measurements and provide feasible technical support for further research or application in cerebral EIT.
ISSN:0090-6964
1573-9686
DOI:10.1007/s10439-011-0302-9