Estimation of wavelet and short-time Fourier transform sonograms of normal and diabetic subjects’ electrogastrogram

Electrogastrography measurement systems and analysis methods used in clinical practice and research: comprehensive review

Electrogastrography (EGG) is a non-invasive method with high diagnostic potential for the prevention of gastroenterological pathologies in clinical practice. In this study, a review of the measurement systems, procedures, and methods of analysis used in electrogastrography is presented. A critical review of historical and current literature is conducted, focusing on electrode placement, measurement apparatus, measurement procedures, and time-frequency domain methods of filtration and analysis of the non-invasively measured electrical activity of the stomach. As a result, 129 relevant articles with primary aim on experimental diet were reviewed in this study. Scopus, PubMed, and Web of Science databases were used to search for articles in English language, according to the specific query and using the PRISMA method. The research topic of electrogastrography has been continuously growing in popularity since the first measurement by professor Alvarez 100 years ago, and there are many researchers and companies interested in EGG nowadays. Measurement apparatus and procedures are still being developed in both commercial and research settings. There are plenty variable electrode layouts, ranging from minimal numbers of electrodes for ambulatory measurements to very high numbers of electrodes for spatial measurements. Most authors used in their research anatomically approximated layout with two++ active electrodes in bipolar connection and commercial electrogastrograph with sampling rate of 2 or 4 Hz. Test subjects were usually healthy adults and diet was controlled. However, evaluation methods are being developed at a slower pace, and usually the signals are classified only based on dominant frequency. The main review contributions include the overview of spectrum of measurement systems and procedures for electrogastrography developed by many authors, but a firm medical standard has not yet been defined. Therefore, it is not possible to use this method in clinical practice for objective diagnosis.

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Parieto-occipital ERP indicators of gut mechanosensation in humans

Understanding the neural processes governing the human gut-brain connection has been challenging due to the inaccessibility of the body's interior. Here, we investigated neural responses to gastrointestinal sensation using a minimally invasive mechanosensory probe by quantifying brain, stomach, and perceptual responses following the ingestion of a vibrating capsule. Participants successfully perceived capsule stimulation under two vibration conditions (normal and enhanced), as evidenced by above chance accuracy scores. Perceptual accuracy improved significantly during the enhanced relative to normal stimulation, which was associated with faster stimulation detection and reduced reaction time variability. Capsule stimulation induced late neural responses in parieto-occipital electrodes near the midline. Moreover, these 'gastric evoked potentials' showed intensity-dependent increases in amplitude and were significantly correlated with perceptual accuracy. Our results replicated in a separate experiment, and abdominal X-ray imaging localized most capsule stimulations to the gastroduodenal segments. Combined with our prior observation that a Bayesian model is capable of estimating computational parameters of gut-brain mechanosensation, these findings highlight a unique form of enterically-focused sensory monitoring within the human brain, with implications for understanding gut feelings and gut-brain interactions in healthy and clinical populations.

Frequency-specific electrogastrography as a non-invasive tool to measure gastrointestinal maturity in preterm infants

Enteral feeding is challenging in preterm infants because of gastrointestinal (GI) immaturity. Electrogastrography (EGG) is a non-invasive technology that measures gastric myoelectrical activity and can be utilized to measure changes that occur with maturation at different gestational ages (GA). Three gastric rhythms (GR) exist between 0.5-9 cycles per minute (cpm), namely, bradygastria (0.5 ≤ GR < 2 cpm), normogastria (2 ≤ GR < 4 cpm), and tachygastria (4 ≤ GR < 9 cpm). We aimed to characterize EGG-derived parameters for different GA by quantifying (1) power spectral density (PSD) and its spectral means at three GR bands (i.e., mPSD_GR) and (2) the percent (%) time spent in each band. Data analyzed was from a longitudinal cohort of preterm infants (n = 51) born at early, mid, and term GA of < 29, 29-33, and ≥ 37 weeks, respectively. Weekly EGG monitoring was performed until 40 weeks' postmenstrual age or discharge. Pre-, during, and post-feed data were analyzed for mPSD_GR at each GR band. Also, % bradygastria, % normogastria, and % tachygastria were calculated by continuous wavelet transform analysis. Results showed (1) mPSD values in normogastria and tachygastria during feeding increased with advancing GA, and (2) % normogastria increased with advancing GA regardless of GR ranges, suggesting EGG may measure GI maturity in preterm infants.

Biosensor-Assisted Method for Abdominal Syndrome Classification Using Machine Learning Algorithm

The digestive system is one of the essential systems in human physiology where the stomach has a significant part to play with its accessories like the esophagus, duodenum, small intestines, and large intestinal tract. Many individuals across the globe suffer from gastric dysrhythmia in combination with dyspepsia (improper digestion), unexplained nausea (feeling), vomiting, abdominal discomfort, ulcer of the stomach, and gastroesophageal reflux illnesses. Some of the techniques used to identify anomalies include clinical analysis, endoscopy, electrogastrogram, and imaging. Electrogastrogram is the registration of electrical impulses that pass through the stomach muscles and regulate the contraction of the muscle. The electrode senses the electrical impulses from the stomach muscles, and the electrogastrogram is recorded. A computer analyzes the captured electrogastrogram (EGG) signals. The usual electric rhythm produces an enhanced current in the typical stomach muscle after a meal. Postmeal electrical rhythm is abnormal in those with stomach muscles or nerve anomalies. This study considers EGG of ordinary individuals, bradycardia, dyspepsia, nausea, tachycardia, ulcer, and vomiting for analysis. Data are collected in collaboration with the doctor for preprandial and postprandial conditions for people with diseases and everyday individuals. In CWT with a genetic algorithm, db4 is utilized to obtain an EGG signal wave pattern in a 3D plot using MATLAB. The figure shows that the existence of the peak reflects the EGG signal cycle. The number of present peaks categorizes EGG. Adaptive Resonance Classifier Network (ARCN) is utilized to identify EGG signals as normal or abnormal subjects, depending on the parameter of alertness (μ). This study may be used as a medical tool to diagnose digestive system problems before proposing invasive treatments. Accuracy of the proposed work comes up with 95.45%, and sensitivity and specificity range is added as 92.45% and 87.12%.

Gut inference: A computational modelling approach

Neurocomputational theories have hypothesized that Bayesian inference underlies interoception, which has become a topic of recent experimental work in heartbeat perception. To extend this approach beyond cardiac interoception, we describe the application of a Bayesian computational model to a recently developed gastrointestinal interoception task completed by 40 healthy individuals undergoing simultaneous electroencephalogram (EEG) and peripheral physiological recording. We first present results that support the validity of this modelling approach. Second, we provide a test of, and confirmatory evidence supporting, the neural process theory associated with a particular Bayesian framework (active inference) that predicts specific relationships between computational parameters and event-related potentials in EEG. We also offer some exploratory evidence suggesting that computational parameters may influence the regulation of peripheral physiological states. We conclude that this computational approach offers promise as a tool for studying individual differences in gastrointestinal interoception.

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

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.

Continuous wavelet analysis of postprandial EGGs suggests sustained gastric slow waves may be slow to develop in infants with colic

BACKGROUND

Electrogastrography in conjunction with Fast Fourier transform has limited success in detecting low grade abnormalities in gastric electrophysiological activity owing to the non-stationarity of the signal. Analysis by continuous wavelet transform is suitable for non-stationary signals and was used to analyse EGG activity in babies with and without colic.

METHODS

Thirty minute postprandial EGG recordings were obtained from 23 sleeping breast-fed infants with clinically validated recurrent colic and 26 breast-fed non-colicky infants. Continuous wavelet transform analysis (CWT) identified three principal frequency components. The mean, standard deviation, and the number of frequency maxima that fell below one standard deviation from the mean were determined for each infant and each frequency.

KEY RESULTS

Three component frequencies in the ranges 1.4-2.5 cpm, 2.5-4.0 cpm, and 4.0-15 cpm were found in all EGGs. Pairwise comparisons of the characteristics of each of the frequency ranges by univariate analyses showed significant differences between colicky and non-colicky subjects only in the number of maxima in the mid range of frequencies that lay below one standard deviation from the mean. However, CWT based on all frequencies allowed discrimination of the EGGS of colicky from non-colicky babies on a basis of number of frequency maxima below one standard deviation from the mean in the midrange of frequencies and in the mean and standard deviation in the low range of frequencies that was likely a harmonic of the midrange.

CONCLUSIONS & INFERENCES

CWT allowed distinction of EGG signals from colicky and healthy babies. The results indicate that colic may result from tardiness in the establishment of coherent propagation of the gastric slow wave in colicky babies.

Current status of multichannel electrogastrography and examples of its use

Electrogastrography (EGG) is a non-invasive diagnostic motility for recording gastric myoelectrical activity. Gastric myoelectrical activity was first recorded in 1922. Advances in recording equipment enabled widespread use of cutaneous EGG after 1985. Later, introduction of multichannel EGG (M-EGG) enabled measurement of electrical activity transmission. At present, M-EGG findings are used as objective indicators of gastric motility disorders caused by various diseases. EGG measures two categories of gastric electrical activity: electrical response activity, or spike potentials; and electrical control activity, or slow waves. The appearance of abnormal rhythmic electrical activity is indicative of abnormalities in gastric motility. The normal frequency range of gastric electrical activity (normogastria) is around 3 cycles per min. Multiple EGG parameters assist in the assessment of gastric myoelectrical activity, and significant correlations between EGG and other gastric motility tests have been demonstrated in many studies. In Japan, however, EGG remains in the exploratory stage, and its clinical use is limited. There are large variations in procedures and systems used in previous studies, thus there is a need for standardization of EGG procedures and technical terminology. Here, we outline the current status of EGG and report the M-EGG procedures used in our department in addition to our M-EGG findings.

The abstract of this manuscript was presented during an educational seminar titled "Current status of gastrointestinal motility tests and keys for immediate implementation" at the 54th Annual Meeting of the Japan Society of Smooth Muscle Research

Reconstruction of gastric slow wave from finger photoplethysmographic signal using radial basis function neural network

Extraction of extra-cardiac information from photoplethysmography (PPG) signal is a challenging research problem with significant clinical applications. In this study, radial basis function neural network (RBFNN) is used to reconstruct the gastric myoelectric activity (GMA) slow wave from finger PPG signal. Finger PPG and GMA (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the sampling rate of 100 Hz from ten healthy subjects. Discrete wavelet transform (DWT) was used to extract slow wave (0-0.1953 Hz) component from the finger PPG signal; this slow wave PPG was used to reconstruct EGG. A RBFNN is trained on signals obtained from six subjects in both fasting and postprandial conditions. The trained network is tested on data obtained from the remaining four subjects. In the earlier study, we have shown the presence of GMA information in finger PPG signal using DWT and cross-correlation method. In this study, we explicitly reconstruct gastric slow wave from finger PPG signal by the proposed RBFNN-based method. It was found that the network-reconstructed slow wave provided significantly higher (P < 0.0001) correlation (≥ 0.9) with the subject's EGG slow wave than the correlation obtained (≈0.7) between the PPG slow wave from DWT and the EEG slow wave. Our results showed that a simple finger PPG signal can be used to reconstruct gastric slow wave using RBFNN method.

Influence of pre-orthodontic trainer treatment on the perioral and masticatory muscles in patients with Class II division 1 malocclusion

The aim of this follow-up study was to evaluate the effects of Pre-Orthodontic Trainer (POT) appliance on the anterior temporal, mental, orbicularis oris, and masseter muscles through electromyography (EMG) evaluations in subjects with Class II division 1 malocclusion and incompetent lips. Twenty patients (mean age: 9.8 ± 2.2 years) with a Class II division 1 malocclusion were treated with POT (Myofunctional Research Co., Queensland, Australia). A group of 15 subjects (mean age: 9.2 ± 0.9 years) with untreated Class II division 1 malocclusions was used as a control. EMG recordings of treatment group were taken at the beginning and at the end of the POT therapy (mean treatment period: 7.43 ± 1.06 months). Follow-up records of the control group were taken after 8 months of the first records. Recordings were taken during different oral functions: clenching, sucking, and swallowing. Statistical analyses were undertaken with Wilcoxon and Mann-Whitney U-tests. During the POT treatment, activity of anterior temporal, mental, and masseter muscles was decreased and orbicularis oris activity was increased during clenching and these differences were found statistically significant when compared to control. Orbicularis oris activity during sucking was increased in the treatment group (P < 0.05). In the control group, significant changes were determined for anterior temporal (P < 0.05) and masseter (P < 0.01) muscle at clenching and orbicularis oris (P < 0.05) muscle at swallowing during observation period. Present findings indicated that treatment with POT appliance showed a positive influence on the masticatory and perioral musculature.

On non-invasive measurement of gastric motility from finger photoplethysmographic signal

This article investigates the possibility of extracting gastric motility (GM) information from finger photoplethysmographic (PPG) signals non-invasively. Now-a-days measuring GM is a challenging task because of invasive and complicated clinical procedures involved. It is well-known that the PPG signal acquired from finger consists of information related to heart rate and respiratory rate. This thread is taken further and effort has been put here to find whether it is possible to extract GM information from finger PPG in an easier way and without discomfort to the patients. Finger PPG and GM (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the rate of 100 Hz from eight healthy subjects for 30 min duration in fasting and postprandial states. In this study, we process the finger PPG signal and extract a slow wave that is analogous to actual EGG signal. To this end, we chose two advanced signal processing approaches: first, we perform discrete wavelet transform (DWT) to separate the different components, since PPG and EGG signals are non-stationary in nature. Second, in the frequency domain, we perform cross-spectral and coherence analysis using autoregressive (AR) spectral estimation method in order to compare the spectral details of recorded PPG and EGG signals. In DWT, a lower frequency oscillation (≈0.05 Hz) called slow wave was extracted from PPG signal which looks similar to the slow wave of GM in both shape and frequency in the range (0-0.1953) Hz. Comparison of these two slow wave signals was done by normalized cross-correlation technique. Cross-correlation values are found to be high (range 0.68-0.82, SD 0.12, R = 1.0 indicates exact agreement, p < 0.05) for all subjects and there is no significant difference in cross-correlation between fasting and postprandial states. The coherence analysis results demonstrate that a moderate coherence (range 0.5-0.7, SD 0.13, p < 0.05) exists between EGG and PPG signal in the "slow wave" frequency band, without any significant change in the level of coherence in postprandial state. These results indicate that finger PPG signal contains GM-related information. The findings are sufficiently encouraging to motivate further exploration of finger PPG as a non-invasive source of GM-related information.

Analysis of the electrogastrogram using discrete wavelet transform and statistical methods to detect gastric dysrhythmia

Electrogastrography (EGG) is a method of recording stomach electrical activity from cutaneous electrodes placed on the abdominal surface. Compared with other electrophysiological measurements, such as electrocardiography, the progress of the applicability of the EGG has been very slow. Unlike imaging or manometrical studies, stomach motility disorders are not diagnosed based only on abnormal EGG parameters. Limitations of EGG recording, processing, computation, acceptable normal parameters, technique and reading should be known to conduct subjective assessments when EGG is used to resolve stomach dysfunction. Therefore appropriate application of non-invasive EGG should go on providing more information and insight in understanding these limitations. And so the aim of this study were to contribute the evolution of the EGG to enter the clinical world as a routine check-up method and to develop new time-frequency analysis method for the detection of gastric dysrhythmia from the EGG.