Evaluation of electrical impedance tomography sensor using internal-external electrodes for small-scale cylindrical root zones

Zhao, Peng-Fei; Fan, Lifeng; Wang, Yongqian; Li, Yang; Wang, Nan; Cheng, Qiang; Wang, Zhongyi; Huang, Lan

doi:10.1016/j.measurement.2022.110874

Cited by 5 publications

(2 citation statements)

References 43 publications

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“…Theoretically, increasing the number of electrodes might be an effective method because more resulting surface potentials could be collected for image reconstruction. However, this not only leads to greater complexity of EIT data acquisition system, but also lengthens the time for data acquisition and image reconstruction (Tawil et al 2011, Czaplik et al 2014, Stowe and Adler 2020, Zhao et al 2022. Another option is to optimize current injection.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system

Yang,

Gao,

Wang

et al. 2024

Physiol. Meas.

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BackgroundWearable electrical impedance tomography (EIT) can be used to monitor regional lung ventilation and perfusion at the bedside. Due to its special system architecture, the amplitude of the injected current is usually limited compared to stationary EIT system. This study aims to evaluate the performance of current injection patterns with various low-amplitude currents in healthy volunteers.MethodsA total of 96 test sets of EIT measurement was recorded in 12 healthy subjects by employing adjacent and opposite current injection patterns with four amplitudes of small current (i.e. 1 mA, 500 uA, 250 uA and 125 uA). The performance of the two injection patterns with various currents was evaluated in terms of signal-to-noise ratio (SNR) of thorax impedance, EIT image metrics and EIT-based clinical parameters.ResultsCompared with adjacent injection, opposite injection had higher SNR (p<0.01), less inverse artifacts (p<0.01), and less boundary artifacts (p<0.01) with the same current amplitude. In addition, opposite injection exhibited more stable EIT-based clinical parameters (p<0.01) across the current range. For adjacent injection, significant differences were found for three EIT image metrics (p<0.05) and four EIT-based clinical parameters (p<0.01) between the group of 125 uA and the other groups.ConclusionFor better performance of wearable pulmonary EIT, currents greater than 250 uA should be used in opposite injection, 500 uA in adjacent one, to ensure a high level of SNR, a high quality of reconstructed image as well as a high reliability of clinical parameters.

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Section: Introductionmentioning

confidence: 99%

Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system

Yang,

Gao,

Wang

et al. 2024

Physiol. Meas.

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“…In addition to solving the ill-posed problem by regularization, intelligent algorithms have also been employed to obtain internal tactile information from the boundary measurements [28,29]. For example, the classification algorithms have been used to achieve a high localization accuracy, but it can only locate one single contact [12].…”

Section: Introductionmentioning

confidence: 99%

Selection of optimal hyperparameter for detecting multiple contacts from large-area tactile sensors based on electrical impedance tomography

et al. 2023

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Large-area tactile sensors based on the technique of electrical impedance tomography (EIT) has drawn considerable interest in human-robot interactions. However, due to the ill-posed condition, it is challenging to differentiate between the real contacts and the artifacts from the reconstructed image. To address this issue, a new method to select an optimal hyperparameter that tunes the amount of regularization is developed in the context of tactile sensing. The optimal hyperparameter is determined to be the minimum value to obtain a stabilized number of sub-regions in the reconstructed image. The proposed method not only guarantees a correct detection on the number of multiple contacts at the minimum amount of regularization, but also provides a proper range of hyperparameters. The optimal hyperparameter is found in a chair-shape relation with the boundary signal-to-noise ratio (SNR), by varying the noise level of the hardware in simulation. The optimal hyperparameter decreases significantly when the boundary SNR increases between 5~10 dB and 25~35 dB, and keeps almost unchanged when SNR is between 10~25 dB. The chair-shape relation also holds for contact conditions with varied intensities and sizes. Experimental validations on the proposed method are conducted on a compliant piezoresistive tactile sensor made of exfoliated graphite polymer composites. By varying the number of contacts in experiments, the relation between the optimal hyperparameter and the boundary SNR is consistent with the chair-shape curve. The investigation made in this work helps improve the performance of identifying multiple contacts from tactile sensors based on electrical impedance tomography.

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Robust electrical impedance tomography for biological application: A mini review

Li¹,

Wang²,

Fan³

et al. 2023

Heliyon

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Evaluation of electrical impedance tomography sensor using internal-external electrodes for small-scale cylindrical root zones

Cited by 5 publications

References 43 publications

Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system

Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system

Selection of optimal hyperparameter for detecting multiple contacts from large-area tactile sensors based on electrical impedance tomography

Robust electrical impedance tomography for biological application: A mini review

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