AD5933-based spectrometer for electrical bioimpedance applications

Ferreira, Joana; Seoane, Fernando; Ansede, Antonio; Bardia, Ramon Bragós

doi:10.1088/1742-6596/224/1/012011

Cited by 40 publications

(15 citation statements)

References 4 publications

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“…Other authors proposed the use of AD5933 to make low-cost biosensor systems for applications in DNA and protein sensing (van Grinsven et al, 2010), detection of bladder cancer (Chuang et al, 2016) and avian flu virus (Wang et al, 2015). Kamat et al (2014) discussed a sensor for non-invasive blood glucose analysis; Ferreira et al proposed an application for total body composition (Ferreira et al, 2010) and body fluid distribution analysis (Ferreira et al, 2011);Park et al (2006) discussed the implementation of a sensor system to monitor civil infrastructures (particularly for loosening bolts in a bolt-jointed structure and detection of corrosion in an aluminum beam); Durante et al (2016) developed a sensor to be used for real-time monitoring to detect fraud in milk composition.…”

Section: Introductionmentioning

confidence: 99%

Electrical impedance spectroscopy (EIS) for biological analysis and food characterization: a review

Grossi

Riccò

2017

J. Sens. Sens. Syst.

311

160

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Abstract. Electrical impedance spectroscopy (EIS), in which a sinusoidal test voltage or current is applied to the sample under test to measure its impedance over a suitable frequency range, is a powerful technique to investigate the electrical properties of a large variety of materials. In practice, the measured impedance spectra, usually fitted with an equivalent electrical model, represent an electrical fingerprint of the sample providing an insight into its properties and behavior. EIS is used in a broad range of applications as a quick and easily automated technique to characterize solid, liquid, semiliquid, organic as well as inorganic materials. This paper presents an updated review of EIS main implementations and applications.

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Section: Introductionmentioning

confidence: 99%

Electrical impedance spectroscopy (EIS) for biological analysis and food characterization: a review

Grossi

Riccò

2017

J. Sens. Sens. Syst.

311

160

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“…The tissue impedance was immediately estimated after applying a current pulse. From the literature, an additional frequency sweep (Aroom et al, 2009;Ferreira et al, 2010;Marsland & Evans, 1987) three-electrode configuration (Organ et al, 1968;Morimoto et al, 1993) is required for bioimpedance analysis. Hence, existing methods may not be suitable for clinical use in real acoustic neuroma surgeries, as they require additional stimulation and specific probe configuration.…”

Section: Discussionmentioning

confidence: 99%

Electrical stimulation‐based nerve location prediction for cranial nerve VII localization in acoustic neuroma surgery

2018

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IntroductionCranial nerve (CN) VII localization is a critical step during acoustic neuroma surgery because the nerve is generally hidden due to the tumor mass. The patient can suffer from Bell's palsy if the nerve is accidentally damaged during tumor removal. Surgeons localize CN VII by exploring the target area with a stimulus probe. Compound muscle action potentials (CMAPs) are elicited when the probe locates the nerve. However, false positives and false negatives are possible due to unpredictable tissue impedance in the operative area. Moreover, a single CMAP amplitude is not correlated with probe‐to‐nerve distance.ObjectivesThis paper presents a new modality for nerve localization. The probe‐to‐nerve distance is predicted by the proposed nerve location prediction model.MethodsInput features are extracted from CMAP responses, tissue impedance, and stimulus current. The tissue impedance is calculated from the estimated resistance and capacitance of the tissue equivalent circuit. In this study, experiments were conducted in animals. A frog's sciatic nerve and gastrocnemius were used to represent CN VII and facial muscle in humans, respectively. Gelatin (2.8%) was used as a mock material to mimic an acoustic neuroma. The %NaCl applied to the mock material was used to emulate uncontrollable impedance of tissue in the operative area.ResultsThe 10‐fold cross‐validation results revealed an average prediction accuracy of 86.71% and an average predicted error of 0.76 mm compared with the measurement data.ConclusionThe proposed nerve location prediction model could predict the probe‐to‐nerve distance across various impedances of the mock material.

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“…The AD5933 chip has been used over the last years in the implementation of several projects such as measuring bioimpedance for pattern recognition and health control (see [25,26]). In order to obtain a resistivity spectra from this chip it is necessary to specify the initial frequency of the sweep, the frequency step and the number of points to be swept.…”

Section: Tested Fluids and Mediumsmentioning

confidence: 99%

Porous medium permeability estimation for well imagery and characterization using complex resistivity spectra

Valentin

Albuquerque

et al. 2018

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Formation permeability plays a crucial role in oil/gas industry as it helps geologists understand how the soil was formed and the most likely location of a certain reservoir. It also aids engineers and analysts to know whether that reservoir is exploitable or not. However, these measurements are very costly and difficult to obtain. In the past decades, several methods have appeared for estimating permeability from different sources like Nuclear Magnetic Resonance data or well-logs. In this work we tested the relationship between complex impedance spectra and permeability measurements, showing that -for the tested porous medium-it does exist a correlation of almost 98% between the obtained complex electrical impedance spectra and the permeability of those mediums. This link could be used in the oil/gas industry adapting the current electrical imaging tools to perform sweep measurements instead of single-frequency measurements, which could be used, in theory, to obtain permeability measurements with spacial resolution. On the other hand, we also designed and implemented an imaging tool that relies on this principle to obtain complex impedance volume images.Keywords: Complex Resistivity Spectra, Permeability Estimation, Porosity, Borehole Image, Oil, Reservoir.Resumo: As medidas de permeabilidade de formação são chave no relacionadoà caracterização de solos. Este parámetro tem um papel fundamental na indústria de gás eóleo, pois ajuda os geólogos a entender como um certo solo foi formado e a possível e mais provável localização de um certo reservatório; e ajuda os engenheiros e analistas a saber se um certo reservatórioé explorável ou não. No entanto, medidas de permeabilidade são muito custosas e difíceis de se obter. Nasúltimas décadas apareceram novos métodos de estimativa da permeabilidade a partir de fontes de dados como Resonância Magnética Nuclear ou logs de poços. Neste trabalho testamos a relação que medidas de impedância complexa têm com medidas de permeabilidade, provando que -para os médios porosos testados-existe uma correlação de quase 98% entre os espectros de impedância complexa obtidos e a permeabilidade desses médios. Esta relação poderia ser utilizada na indústria deóleo e gás adaptando os sistemas de imageamento elétricos atuais para realizar varreduras de frequência, ao invés de medidas monofrequenciais, as quais poderiam ser posteriormente usadas para criar imagens de permeabilidade estimada. Por outro lado, também realizamos o design e implementação de uma ferramenta de imageamento baseada no princípio de obtenção de imagens de espectros complexos impedância elétrica.

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AD5933-based spectrometer for electrical bioimpedance applications

Cited by 40 publications

References 4 publications

Electrical impedance spectroscopy (EIS) for biological analysis and food characterization: a review

Electrical impedance spectroscopy (EIS) for biological analysis and food characterization: a review

Electrical stimulation‐based nerve location prediction for cranial nerve VII localization in acoustic neuroma surgery

Porous medium permeability estimation for well imagery and characterization using complex resistivity spectra

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