Frequency Analysis of Bioimpedance Signals Applied to the Field of Urology: A Pilot Study
DOI:
https://doi.org/10.13053/cys-29-2-5704Keywords:
Urinary bladder volume, frequency analysis, bioimpedance, Lissajous plotsAbstract
Currently, urodynamics is the technique used for monitoring bladder volume, as it allows the diagnosis of various bladder pathologies such as neurogenic bladder dysfunction. This technique has limitations, including invasiveness and limited ability to detect dynamic changes. Electrical bioimpedance (EBI) emerges as a non-invasive alternative that measures changes in the electrical impedance of biological tissue in response to variations in bladder volume and composition. In this study, a frequency analysis was proposed to identify and compare changes between voided and full bladder using the EBI technique. Bladder filling was monitored in a group of 5 healthy participants by measuring the EBI vector parameters at a frequency of 50 kHz using two pairs of surface electrodes (Ag/AgCl Ambiderm T125). The data at the beginning and end of the measurement were converted to the frequency domain using the Fourier transform, thereby obtaining the frequency spectra. The dominant harmonic in the frequency signals was identified by applying a Gaussian mask, which allowed for filtering the signals and detecting significant patterns and characteristics in bladder impedance. A decrease in the amplitude of the signals was observed after filling, which could indicate a reduction in the reactivity of bladder tissue to electrical stimuli as the bladder fills. With these results, we can conclude that EBI, combined with frequency analysis, allows for the characterization of bladder filling, offering a non-invasive and detailed alternative for monitoring bladder function, with the potential to improve the diagnosis and management of bladder pathologies.Downloads
Published
2025-06-18
Issue
Section
Articles of the Thematic Section
License
Hereby I transfer exclusively to the Journal "Computación y Sistemas", published by the Computing Research Center (CIC-IPN),the Copyright of the aforementioned paper. I also accept that these
rights will not be transferred to any other publication, in any other format, language or other existing means of developing.I certify that the paper has not been previously disclosed or simultaneously submitted to any other publication, and that it does not contain material whose publication would violate the Copyright or other proprietary rights of any person, company or institution. I certify that I have the permission from the institution or company where I work or study to publish this work.The representative author accepts the responsibility for the publicationof this paper on behalf of each and every one of the authors.
This transfer is subject to the following conditions:- The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
- Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
- Authors may include working as part of his thesis, for non-profit distribution only.