Impedance Ratio Method for Urine Conductivity-Invariant Estimation of Bladder Volume

Schlebusch, Thomas; Orschulik, Jakob; Malmivuo, Jaakko; Leonhardt, Steffen; Leonhäuser, Dorothea; Grosse, Joachim; Kowollik, Michael; Kirschner‐Hermanns, Ruth; Walter, Marian

doi:10.5617/jeb.895

Cited by 20 publications

(37 citation statements)

References 12 publications

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“…The data presented herein (Table 5) show that for a constant fluid volume significant differences (p < 0.05) in GI values follow conductivity changes. These results are in agreement with previous studies [8], [12], indicating that GI can be used to estimate volumes only when conductivity of the object under study remains constant.…”

Section: Discussionsupporting

confidence: 93%

Robustness of focused and global impedance estimates of bladder volumes against uncertainty of urine conductivity

Leyton

Bardia

Rodas

2020

Biomed. Phys. Eng. Express

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Bioimpedance measurements are currently used to monitor various biological processes and are potentially useful for studies of urodynamics. Global impedance (GI) and focused impedance measurements (FIM) can be used to monitor bladder volumes, but these are subject to varying conductivity of urine. To address this, we emulated a human bladder using an agar phantom filled with saline solutions of varying conductivities and estimated volumes using a modified FIM-based approach. Using this novel strategy, electrical potentials did not change significantly with constant liquid volumes, even when the conductivity of the saline solutions was varied between 1.027 to 1.877 and 2.610 S/m. Conversely, GI and classic FIM measurements of constant liquid volumes varied with conductivity. These observations suggest that the proposed FIM approach is suitable for bladder volume estimation due to its robustness against uncertainties of conductivity. The bioimpedance hardware used in our experiments comprised 8 electrodes and a a small and low cost impedance measurement system based on an AFE4300 direct impedance measurement device.

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Section: Discussionsupporting

confidence: 93%

Robustness of focused and global impedance estimates of bladder volumes against uncertainty of urine conductivity

Leyton

Bardia

Rodas

2020

Biomed. Phys. Eng. Express

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“…The conductivity of the thin bladder wall was discounted, and the conductivity of the bladder was considered the same as the conductivity of urine. The urine conductivity range aligns with the range of urine conductivities reported in the current literature 24 , 26 – 28 .…”

Section: Simulation Data Generationsupporting

confidence: 86%

Supervised Learning Classifiers for Electrical Impedance-based Bladder State Detection

Dunne

Santorelli

McGinley

et al. 2018

Sci Rep

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Urinary Incontinence affects over 200 million people worldwide, severely impacting the quality of life of individuals. Bladder state detection technology has the potential to improve the lives of people with urinary incontinence by alerting the user before voiding occurs. To this end, the objective of this study is to investigate the feasibility of using supervised machine learning classifiers to determine the bladder state of ‘full’ or ‘not full’ from electrical impedance measurements. Electrical impedance data was obtained from computational models and a realistic experimental pelvic phantom. Multiple datasets with increasing complexity were formed for varying noise levels in simulation. 10-Fold testing was performed on each dataset to classify ‘full’ and ‘not full’ bladder states, including phantom measurement data. Support vector machines and k-Nearest-Neighbours classifiers were compared in terms of accuracy, sensitivity, and specificity. The minimum and maximum accuracies across all datasets were 73.16% and 100%, respectively. Factors that contributed most to misclassification were the noise level and bladder volumes near the threshold of ‘full’ or ‘not full’. This paper represents the first study to use machine learning for bladder state detection with electrical impedance measurements. The results show promise for impedance-based bladder state detection to support those living with urinary incontinence.

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“…They proposed a method based on machine learning by training the measured voltages [3] and the reconstructed EIT images [8] to determine the bladder status. Schlebusch et al found that urine conductivity significantly affects the measurement accuracy of bladder volume by EIT [9]. He et al simulated a planar electrode array to image the bladder in three-dimension (3D), which obtained the information about the bladder location in the third dimension [10].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Bladder Volume Measurement Based on Fringe Effect of Electrical Impedance Tomography Sensors

Liu

Bai

Wei

et al. 2022

IEEE Open J. Instrum. Meas.

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Patients with bladder dysfunction are unable to perceive bladder volume and urinate spontaneously, and hence usually require catheterization. Personalized catheterization can effectively reduce the risk of urinary tract infections caused by catheterization. Electrical impedance tomography (EIT) can provide an effective tool for personalized catheterization by monitoring bladder volume. This study exploits the fringe effect of a 2D EIT sensor to derive the 3D volumetric information about bladder and improve the measurement consistency and accuracy of bladder volume under varied urine conductivities. The EIT sensor is optimized regarding the specified application of fringe effect. The parameters to be optimized include the electrode arrangement, the distance of electrode plane from bladder bottom, and the number of electrodes. Three evaluation criteria are proposed for the optimization. Simulation and experiment confirm the feasibility of the fringe effect-based method for bladder volume measurement, and the performances of the optimized sensor are illustrated. It is concluded that the fringe effect-based method has a better measurement consistency and accuracy against urine conductivity than the widely-used global impedancebased method, and hence provides a new promising alternative for bladder volume measurement.

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Impedance Ratio Method for Urine Conductivity-Invariant Estimation of Bladder Volume

Cited by 20 publications

References 12 publications

Robustness of focused and global impedance estimates of bladder volumes against uncertainty of urine conductivity

Robustness of focused and global impedance estimates of bladder volumes against uncertainty of urine conductivity

Supervised Learning Classifiers for Electrical Impedance-based Bladder State Detection

Investigation of Bladder Volume Measurement Based on Fringe Effect of Electrical Impedance Tomography Sensors

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