Diagnosis of gastric disorders by non-invasive myoelectrical measurements

Morello, Rosario; Capua, C. De; Lamonaca, Francesco

doi:10.1109/i2mtc.2013.6555628

Cited by 11 publications

(10 citation statements)

References 24 publications

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“…All the subjects were requested to stay awake without talking or reading and they tried to remain as still as possible throughout the recording time to minimize movement artifacts. 1,4,32 The filter characteristics of the amplifier allowed those signals with an approximate frequency range of 1-15 cpm to pass through for recording and digitization. Two channels of data were recorded during the session.…”

Section: Egg Recording Proceduresmentioning

confidence: 99%

Analysis of gastric myoelectrical activity from the electrogastrogram signals based on wavelet transform and line length feature

Kafee

Akan

2018

Proc Inst Mech Eng H

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Electrogastrogram is used for the abdominal surface measurement of the gastric electrical activity of the human stomach. The electrogastrogram technique has significant value as a clinical tool because careful electrogastrogram signal recordings and analyses play a major role in determining the propagation and coordination of gastric myoelectric abnormalities. The aim of this article is to evaluate electrogastrogram features calculated by line length features based on the discrete wavelet transform method to differentiate healthy control subjects from patients with functional dyspepsia and diabetic gastroparesis. For this analysis, the discrete wavelet transform method was used to extract electrogastrogram signal characteristics. Next, line length features were calculated for each sub-signal, which reflect the waveform dimensionality variations and represent a measure of sensitivity to differences in signal amplitude and frequency. The analysis was carried out using a statistical analysis of variance test. The results obtained from the line length analysis of the electrogastrogram signal prove that there are significant differences among the functional dyspepsia, diabetic gastroparesis, and control groups. The electrogastrogram signals of the control subjects had a significantly higher line length than those of the functional dyspepsia and diabetic gastroparesis patients. In conclusion, this article provides new methods with increased accuracy obtained from electrogastrogram signal analysis. The electrogastrography is an effective and non-stationary method to differentiate diabetic gastroparesis and functional dyspepsia patients from the control group. The proposed method can be considered a key test and an essential computer-aided diagnostic tool for detecting gastric myoelectric abnormalities in diabetic gastroparesis and functional dyspepsia patients.

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Section: Egg Recording Proceduresmentioning

confidence: 99%

Analysis of gastric myoelectrical activity from the electrogastrogram signals based on wavelet transform and line length feature

Kafee

Akan

2018

Proc Inst Mech Eng H

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“…The EMG monitoring area has advanced in electrodes’ combination for smart sensors, as in a device that uses EMG signals from the stomach, which records signals from the activity of the stomach noninvasively [114,162]. Moreover, for monitoring kinesiological functions, neuromuscular diseases, and motor activity disorders, [163] a smart sensor is presented with electrodes constructed on a printed circuit board.…”

Section: Biomedical Applicationsmentioning

confidence: 99%

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Mendes

Vieira

Pires

et al. 2016

Sensors

101

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The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports), it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others.

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“…In this sight, the authors have focused their research activity on such aspects in order to overcome limitations and lack in the interpretation of the EGG waveforms. So, the authors have proposed in [24] an innovative diagnostic model for characterizing gastric myoelectrical abnormalities due to disorders, and gained long-standing experience in recording of myoelectrical signals, [25]- [27].…”

Section: Introductionmentioning

confidence: 99%

“…The EGG sensing system has been projected and developed according to the Measurement System Design Model described in [28]. The system acquires and processes gastric myoelectrical waves in compliance with the diagnostic model presented in [24]. Then the system decides among five alternative diagnoses.…”

Section: Introductionmentioning

confidence: 99%

Design of a non-invasive sensing system for diagnosing gastric disorders

et al. 2021

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Gastric disorders are widely spread among the population of any age. At the moment, the diagnosis is made by using invasive systems that cause several side effects. The present manuscript proposes an innovative non-invasive sensing system for diagnosing gastric dysfunctions. The Electro-GastroGraphy (EGG) technique is used to record myoelectrical signals of stomach activities. Although EGG technique is well known for a long time, several issues concerning the signal processing and the definition of suitable diagnostic criteria are still unresolved. So, EGG is to this day a trial practice. The authors want to overcome the current limitations of the technique and improve its relevance. To this purpose, a smart EGG sensing system has been designed to non-invasively diagnose gastric disorders. In detail, the system records the gastric slow waves by means of skin surface electrodes placed in the epigastric area. Cutaneous myoelectrical signals are so acquired from the body surface in proximity of stomach. Electro-gastrographic record is then processed. According to the diagnostic model designed from the authors, the system estimates specific diagnostic parameters in time and frequency domains. It uses Discrete Wavelet Transform to obtain power spectral density diagrams. The frequency and power of the EGG waveform and the dominant frequency components are so analyzed. The defined diagnostic parameters are put in comparison with the reference values of a normal EGG in order to estimate the presence of gastric pathologies by the analysis of arrhythmias (<em>tachygastria</em>, <em>bradygastria</em> and irregular rhythm). The paper aims to describe the design of the system and of the arrhythmias detection algorithm. Prototype development and experimental data will be presented in future works. Preliminary results show an interesting relevance of the suggested technique so that it can be considered as a promising non-invasive tool for diagnosing gastrointestinal motility disorders.

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Diagnosis of gastric disorders by non-invasive myoelectrical measurements

Cited by 11 publications

References 24 publications

Analysis of gastric myoelectrical activity from the electrogastrogram signals based on wavelet transform and line length feature

Analysis of gastric myoelectrical activity from the electrogastrogram signals based on wavelet transform and line length feature

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Design of a non-invasive sensing system for diagnosing gastric disorders

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