An Application Supporting Gastroesophageal Multichannel Intraluminal Impedance-pH Analysis

Tojza, Piotr; Gradolewski, Dawid; Redlarski, Grzegorz

doi:10.5220/0005050402310238

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…To measure the quality of the assessment, the typical medical parameters were used: sensitivity and specificity [2,5,6]. Sensitivity (1) is measured as the percentage of correctly diagnosed sick patients (true positives).…”

Section: Wavelet Transformmentioning

confidence: 99%

“…The main disadvantage, however, is the fact that the 24-h dataset has to be assessed by a specialist/gastroenterologist, which can be a time-consuming task. Even with the use of modern computer programs, it takes up to several hours to assess the data [5][6][7][8][9][10]. Therefore, it is advisable to develop computer techniques that will allow the automation of the process and shorten the time needed to diagnose a patient by a specialist.…”

Section: Introductionmentioning

confidence: 99%

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Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease

et al. 2022

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In this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions of such an analysis can sometimes be too subjective. There is no strict procedure or reference values to follow when the impedance measurements are assessed. Therefore, an attempt was made to develop a point of reference for the assessment process, helping to distinguish healthy patients from GERD patients. In this approach, wavelet transform (WT) and wavelet-based fractal analysis (WBFA) were used to aid the diagnostic process. With this approach, it was possible to develop two efficient computer methods to classify healthy and sick patients based on the pH measurement data alone. The WT method provided a sensitivity value of 93.33%, with 75% specificity. The results of the fractal analysis confirmed that the tested signals have features that enable their automatic classification and assignment to a group of sick or healthy people. The article will be interesting for those studying the application of wavelet and fractal analysis in biomedical waveforms. The authors included in the work a description of the implementation of the fractal and wavelet analysis, the descriptions of the results of the analyses, and the conclusions drawn from them. The work will also be of interest to those who study the methods of using machine learning and artificial intelligence in computer-aided, automatic medical diagnostics.

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Section: Wavelet Transformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease

et al. 2022

Self Cite

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“…These methods are characterized by a very high percentage of correctly diagnosed patients, but their main drawback is the time needed by a specialist gastroenterologist to evaluate the results of the measurement. Analysis of 24-hour format pH and impedance is a tedious and time-consuming task, that reduces the time the physician can spend on treating other patients or performing studies [6], [7], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Supporting gastroesophageal reflux disease diagnostics by using wavelet analysis in esophageal pH-metry

Tojza

Redlarski

Janiak

2018

Annals of Computer Science and Information Systems

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This paper presents a new approach to computer supported esophageal pH-metry measurement analysis performed in order to diagnose gastroesophageal reflux disease. In this approach wavelet analysis was used to analyse the esophageal pH-metry course. The research was performed on three groups of pH-metry courses: whole 24-hour pH-metry course, sleep only pH-metry course and 20 minutes after the end of a meal pHmetry course. After performing a 128 level decomposition of the pH-metry course, the Wx was defined as a parameter of extreme differential. This parameter was used to distinguish patients esophageal pH-metry results and on that basis classify patients as healthy or sick. Using this method the sensitivity of 77% was achieved.

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An Application Supporting Gastroesophageal Multichannel Intraluminal Impedance-pH Analysis

Cited by 2 publications

References 9 publications

Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease

Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease

Supporting gastroesophageal reflux disease diagnostics by using wavelet analysis in esophageal pH-metry

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