Gastric functional monitoring by gastric electrical impedance tomography (gEIT) suit with dual-step fuzzy clustering

Abstract

Gastric Function has been successfully estimated by gastric electrical impedance tomography (gEIT) Suit with dual-step fuzzy clustering. The gEIT Suit which are made of elastic cloth with dual-planar electrodes and compact data acquisition (DAQ) system measures gastric impedance Z to visualize the gastric conductivity distribution σ. The dual-step fuzzy clustering extracts the clustered gastric conductivity distribution kσ, which accurately estimates the gastric function. The gEIT Suit with dual-step fuzzy clustering are applied to eight healthy persons during liquid meal consumption to estimate the gastric function under gastric accommodation phase of 200, 400 and 600 mL based on the gastric emptying phase. As the results, the gEIT Suit successfully estimate the gastric function. By the measured impedance Z, the subjects have a mean temporal impedance $$\overline{\Delta \mathbf{Z} }$$ Δ Z ¯ = − 9.27 [Ohm] and p-value of that $$\overline{\mathbf{Z} }$$ Z ¯ p(Z) = 0.0013[–]as the t-test result. In the case of gastric conductivity distribution σ, the subjects have a value of spatial mean conductivity distribution ⟨σ⟩ = 0.23[–] and p-value of that ⟨σ⟩ p(σ) = 0.0140[–]. Lastly, in the case gastric volume V, subjects have a gastric volume V = 12.44 [%] and p-value p(V) = 0.0664[–].

Sodium concentration imaging in dermis layer by square-wave open electrical impedance tomography (SW-oEIT) with spatial voltage thresholding (SVT)

“…where e is permittivity. Assuming that the experiments are static, with no change over time (i.e., ∂t = 0), equation (11) is transformed into the following equation,…”

“…In image visualization of EIT, the measured voltage on the object boundary is used to calculate the conductivity distribution based on the conductivity reconstruction model [10]. EIT has been widely applied in the monitoring of many biomedical processes, such as functional gastric shape [11], breast cancer [12], neural activity [13], and brain imaging [14]. However, the conventional EIT which is based on sinewave injection, has a limitation for imaging the sodium concentration in the dermis layer.…”

Advances in Electrical Impedance Tomography Inverse Problem Solution Methods: From Traditional Regularization to Deep Learning

“…Some representative examples can be found in prostate imaging and breast tomography [6]- [8]. Furthermore, EIT finds space in a variety of other medical or industrial applications, such as gastric-emptying monitoring [9], bladder monitoring [10] and non-destructive evaluation [11].…”

Evaluation of injection current frequency on molten NaCl solidification images reconstructed by high-temperature electrical resistance tomography

“…Besides, at all current frequencies the measured voltage is affected by bulk noise bn E (T) [17] as well as capacitance generated by the htERT device [18]. For instance, general ERT injects alternating current with medium frequencies such as f = 1 kHz for carbon particles in battery slurry during mixing [19], f = 2 kHz for particle deposition imaging in centrifugal fields [20], f = 100-200 kHz for human gastric imaging [21] and f = 1 MHz for cell spheroid imaging [22] to obtain a frequency response based on the object's physical properties. However, each frequency is empirically determined on a case-by-case basis and not evaluated quantitatively by noise analysis at the different frequencies.…”