The extraction of the new components from electrogastrogram (EGG), using both adaptive filtering and electrocardiographic (ECG) derived respiration signal

Electrogastrographic examination (EGG) is a noninvasive method for an investigation of a stomach slow wave propagation. The typical range of frequency for EGG signal is from 0.015 to 0.15 Hz or (0.015–0.3 Hz) and the signal usually is captured with sampling frequency not exceeding 4 Hz. In this paper a new approach of method for recording the EGG signals with high sampling frequency (200 Hz) is proposed. High sampling frequency allows collection of signal, which includes not only EGG component but also signal from other organs of the digestive system such as the duodenum, colon as well as signal connected with respiratory movements and finally electrocardiographic signal (ECG). The presented method allows improve the quality of analysis of EGG signals by better suppress respiratory disturbance and extract new components from high sampling electrogastrographic signals (HSEGG) obtained from abdomen surface. The source of the required new signal components can be inner organs such as the duodenum and colon. One of the main problems that appear during analysis the EGG signals and extracting signal components from inner organs is how to suppress the respiratory components. In this work an adaptive filtering method that requires a reference signal is proposed.Electrogastrographic examination (EGG) is a noninvasive method for an investigation of a stomach slow wave propagation. The typical range of frequency for EGG signal is from 0.015 to 0.15 Hz or (0.015–0.3 Hz) and the signal usually is captured with sampling frequency not exceeding 4 Hz. In this paper a new approach of method for recording the EGG signals with high sampling frequency (200 Hz) is proposed. High sampling frequency allows collection of signal, which includes not only EGG component but also signal from other organs of the digestive system such as the duodenum, colon as well as signal connected with respiratory movements and finally electrocardiographic signal (ECG). The presented method allows improve the quality of analysis of EGG signals by better suppress respiratory disturbance and extract new components from high sampling electrogastrographic signals (HSEGG) obtained from abdomen surface. The source of the required new signal components can be inner organs such as the duodenum and colon. One of the main problems that appear during analysis the EGG signals and extracting signal components from inner organs is how to suppress the respiratory components. In this work an adaptive filtering method that requires a reference signal is proposed

Gastroesophageal reflux in cystic fibrosis across the age spectrum.

Background:Scientific advances have improved longevity in cystic fibrosis (CF) patients and many of these patients can expect to experience age-related gastrointestinal co-morbidities. We aimed to assess the extent to which age might impact gastroesophageal reflux (GER) in patients with CF. Methods:Our esophageal pH-multichannel intraluminal impedance monitoring database was searched for tracings belonging to CF patients ≥2 years old without prior fundoplication and not taking anti-reflux medications immediately prior (within 7 days) and during the study. Tracings were retrospectively analyzed; Impedance and pH variables were evaluated with respect to age and pulmonary function. Results:Twenty-eight patients were enrolled; 16 children (3.1-17.7 years) and 12 adults (18.2-48.9 years). Among pH probe parameters, correlation analysis showed DeMeester score (P=0.011) and number of acid reflux events lasting >5 minutes (P=0.047) to be significantly correlated with age. Age was not significantly correlated with any of the impedance parameters. Age was negatively correlated with baseline impedance (BI) in the distal esophagus (r=-0.424, P=0.023) and BI was negatively correlated with several pH parameters, including reflux index (r=-0.553, P=0.002), number of total acid reflux events (r=-0.576, P=0.001), number of acid reflux events lasting >5 minutes (r=-0.534, P=0.003), and DeMeester score (r=-0.510, P=0.006). Pulmonary function (percent predicted forced expiratory volume in one minute; ppFEV1) was negatively correlated with age (r=-0.494, P=0.0007). The interaction of age and ppFEV1 and any of the reflux parameters, however, was not significant (P>0.05); the strongest evidence for an interaction was found for the number of acid reflux events reaching the proximal esophagus, but this interaction still did not reach statistical significance (P=0.070). Conclusions:In a small cohort, we found evidence that age may be associated with increased acid exposure and that both age and increased acid exposure are associated with reduced BI in the distal esophagus. The negative relationship between pulmonary function and age in our cohort is not related to GER. This pilot study supports the need for esophageal assessment and treatment of GER as standard components of clinical care for an aging CF population

Enhancement of the non-invasive electroenterogram to identify intestinal pacemaker activity

Surface recording of electroenterogram (EEnG) is a non-invasive method for monitoring intestinal myoelectrical activity. However, surface EEnG is seriously affected by a variety of interferences: cardiac activity, respiration, very low frequency components and movement artefacts. The aim of this study is to eliminate respiratory interference and very low frequency components from external EEnG recording by means of empirical mode decomposition (EMD), so as to obtain more robust indicators of intestinal pacemaker activity from external EEnG signal. For this purpose, 11 recording sessions were performed in an animal model under fasting conditions and in each individual session the myoelectrical signal was recorded simultaneously in the intestinal serosa and the external abdominal surface in physiological states. Various parameters have been proposed for evaluating the efficacy of the method in reducing interferences: the signal-to-interference ratio (S/I ratio), attenuation of the target and interference signals, the normal slow wave percentage and the stability of the dominant frequency (DF) of the signal. The results show that the S/I ratio of the processed signals is significantly greater than the original values (9.66±4.44 dB vs. 1.23±5.13 dB), while the target signal was barely attenuated (-0.63±1.02 dB). The application of the EMD method also increased the percentage of the normal slow wave to 100% in each individual session and enabled the stability of the DF of the external signal to be increased considerably. Furthermore, the variation coefficient of the DF derived from the external processed signals is comparable to the coefficient obtained using internal recordings. Therefore the EMD method could be a very useful tool to improve the quality of external EEnG recording in the low frequency range, and therefore to obtain more robust indicators of the intestinal pacemaker activity from non invasive EEnG recordingsThe authors would like to thank D Alvarez-Martinez, Dr C Vila and the Veterinary Unit of the Research Centre of 'La Fe' University Hospital (Valencia, Spain), where the surgical interventions and recording sessions were carried out, and the R+D+I Linguistic Assistance Office at the UPV for their help in revising this paper. This research study was sponsored by the Ministerio de Ciencia y Tecnologia de Espana (TEC2007-64278) and by the Universidad Politecnica de Valencia, as part of a UPV research and development Grant Programme.Ye Lin, Y.; Garcia Casado, FJ.; Prats Boluda, G.; Ponce, JL.; Martínez De Juan, JL. (2009). Enhancement of the non-invasive electroenterogram to identify intestinal pacemaker activity. 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Artifact Rejection Methodology Enables Continuous, Noninvasive Measurement of Gastric Myoelectric Activity in Ambulatory Subjects.

The increasing prevalence of functional and motility gastrointestinal (GI) disorders is at odds with bottlenecks in their diagnosis, treatment, and follow-up. Lack of noninvasive approaches means that only specialized centers can perform objective assessment procedures. Abnormal GI muscular activity, which is coordinated by electrical slow-waves, may play a key role in symptoms. As such, the electrogastrogram (EGG), a noninvasive means to continuously monitor gastric electrical activity, can be used to inform diagnoses over broader populations. However, it is seldom used due to technical issues: inconsistent results from single-channel measurements and signal artifacts that make interpretation difficult and limit prolonged monitoring. Here, we overcome these limitations with a wearable multi-channel system and artifact removal signal processing methods. Our approach yields an increase of 0.56 in the mean correlation coefficient between EGG and the clinical "gold standard", gastric manometry, across 11 subjects (p < 0.001). We also demonstrate this system's usage for ambulatory monitoring, which reveals myoelectric dynamics in response to meals akin to gastric emptying patterns and circadian-related oscillations. Our approach is noninvasive, easy to administer, and has promise to widen the scope of populations with GI disorders for which clinicians can screen patients, diagnose disorders, and refine treatments objectively

Data Augmentation for Generating Synthetic Electrogastrogram Time Series

Objective: To address an emerging need for large amount of diverse datasets for proper training of artificial intelligence (AI) algorithms and for rigor evaluation of signal processing techniques, we developed and evaluated a new method for generating synthetic electrogastrogram (EGG) time series. Methods: We used EGG data from an open database to set model parameters and statistical tests to evaluate synthesized data. Additionally, we illustrated method customization for generating artificial EGG alterations caused by the simulator sickness. Results: Proposed data augmentation method generates synthetic EGG with specified duration, sampling frequency, recording state (postprandial or fasting state), overall noise and breathing artifact injection, and pauses in the gastric rhythm (arrhythmia occurrence) with statistically significant difference between postprandial and fasting states in >70% cases while not accounting for individual differences. Features obtained from the synthetic EGG signal resembling simulator sickness occurrence displayed expected trends. Conclusion: The code for generation of synthetic EGG time series is freely available and can be further customized to assess signal processing algorithms or to increase diversity in datasets used to train AI algorithms. The proposed approach is customized for EGG data synthesis, but can be easily utilized for other biosignals with similar nature such as electroencephalogram.Comment: three figures and two table

Методе за оцену електричне активности глатких мишића

Recording of the smooth stomach muscles' electrical activity can be performed by means of Electrogastrography (EGG), a non-invasive technique for acquisition that can provide valuable information regarding the functionality of the gut. While this method had been introduced for over nine decades, it still did not reach its full potential. The main reason for this is the lack of standardization that subsequently led to the limited reproducibility and comparability between different investigations. Additionally, variability between many proposed recording approaches could make EGG unappealing for broader application. The aim was to provide an evaluation of a simplified recording protocol that could be obtained by using only one bipolar channel for a relatively short duration (20 minutes) in a static environment with limited subject movements. Insights into the most suitable surface electrode placement for EGG recording was also presented. Subsequently, different processing methods, including Fractional Order Calculus and Video-based approach for the cancelation of motion artifacts – one of the main pitfalls in the EGG technique, was examined. For EGG, it is common to apply long-term protocols in a static environment. Our second goal was to introduce and investigate the opposite approach – short-term recording in a dynamic environment. Research in the field of EGG-based assessment of gut activity in relation to motion sickness symptoms induced by Virtual Reality and Driving Simulation was performed. Furthermore, three novel features for the description of EGG signal (Root Mean Square, Median Frequency, and Crest Factor) were proposed and its applicability for the assessment of gastric response during virtual and simulated experiences was evaluated. In conclusion, in a static environment, the EGG protocol can be simplified, and its duration can be reduced. In contrast, in a dynamic environment, it is possible to acquire a reliable EGG signal with appropriate recommendations stated in this Doctoral dissertation. With the application of novel processing techniques and features, EGG could be a useful tool for the assessment of cybersickness and simulator sickness.Снимање електричне активности глатких мишића желуца може се реализовати употребом електрогастрографије (ЕГГ), неинвазивне методе која пружа значајне информације везане за функционисање органа за варење. Упркост чињеници да је откривена пре више од девет деценија, ова техника још увек није остварила свој пун потенцијал. Основни разлог за то је недостатак стандардизације који условљава ограничења у смислу поновљивости и упоредивости између различитих истраживања. Додатно, варијабилност која је присутна у примени различитих препоручених поступака снимања, може смањити интерес за употребу ЕГГ-а код широког опсега потенцијалних корисника. Наш циљ је био да пружимо евалуацију поједностављене методе мерења тј. протокола који укључује само један канал током релативно кратког временског периода (20 минута) у статичким условима са ограниченим кретањем субјекта тј. у мировању. Такође, приказали смо наше ставове у вези најприкладније позиције површинских електрода за ЕГГ снимање. Презентовали смо и резултате испитивања метода, на бази обраде видео снимка као и фракционог диференцијалног рачуна, за отклањање артефаката помераја – једног од највећих изазова са којима је суочена ЕГГ метода. За ЕГГ је уобичајено да се користе дуготрајни протоколи у статичким условима. Наш други циљ био је да представимо и оценимо употребљивост супротног приступа – краткотрајних снимања у динамичким условима. Реализовали смо истраживање на пољу оцене активности желуца током појаве симптома мучнине изазване виртуелном реалношћу и симулацијом вожње. За потребе методе за оцену електричне активности желуца, предложили смо три нова параметра за квантификацију ЕГГ сигнала (ефективну вредност амплитуде, медијану и крест фактор) и извршили процену њихове прикладности за оцену гастроинтестиналног тракта током коришћења виртуелне реалности и симулатора вожње. Закључак је да ЕГГ протокол у статичким условима може бити упрошћен и његово трајање може бити редуковано, док је у динамичким условима могуће снимити одговарајући ЕГГ сигнал, али уз праћење препорука наведених у овој тези. Употребом нових техника за процесирање сигнала и прорачун одговарајућих параметара, ЕГГ може бити корисна техника за оцену мучнине изазване коришћењем симулатора и производа виртуелне реалност

Effects of varying acupuncture manipulations at ST36 (Zusanli) on gastric electrical frequency and amplitude in bradygastria rabbits

Objective. To observe the effects of different manual acupuncture (MA) manipulation on gastric electrical amplitude and frequency for noradrenaline-induced bradygastria in rabbits. Methods. A total of 60 rabbits were randomly allocated into six groups: four MA manipulation groups; reinforcing by twisting the manipulation group (FTG), reducing by twisting the manipulation group (RTG), reinforcing by lifting and thrusting the manipulation group (FLG), and reducing by lifting and thrusting the manipulation group (RLG), a control group (CG), and a model group (MG). The total treatment time length was 45 minutes. The bradygastria was induced via administration of noradrenaline via the marginal ear vein of the rabbits at 5 minutes from baseline, and the bradygastria model was established at 12 minutes from baseline. The rabbits in the four MA manipulation groups received different stimulation parameters at ST36 (Zusanli) for a duration of 3 minutes in accordance with their respective group allocation. The needles were then retained without further manipulation for a further 25 minutes. Gastric electrical amplitude and frequency were recorded using a data acquisition system (Biopac System MP150) at five different time points: baseline (for a duration of 5 minutes), after the bradygastria model was established at 12 minutes from baseline (for a duration of 5 minutes), during MA manipulation commencing at 17 minutes from baseline (for a duration of 3 minutes), 5 minutes after MA manipulation at 25 minutes from baseline (for a duration of 5 minutes), and at 20 minutes following MA manipulation at 40 minutes from baseline (for a duration of 5 minutes). Results. After noradrenaline induction, gastric electrical frequency levels in MA and MG groups were significantly decreased compared to the CG group (P 0.05). During MA manipulation, gastric electrical frequency levels in RTG, FLG, and RLG groups were higher than in the MG group (P < 0.05). At 5 minutes after MA manipulation, gastric electrical frequency levels in RTG and FLG groups were higher than in the MG group (P < 0.05), and gastric electrical frequency level in the RTG group was higher than in the CG group (P < 0.05). At 20 minutes after MA manipulation, gastric electrical frequency levels in FTG, RTG, and FLG groups were higher than in the MG group (P < 0.05). Conclusion. All four variations of MA manipulations have a recovery effect on the gastric electrical frequency of rabbits with bradygastria. In particular, results indicated that FTG, RTG, and FLG at ST36 may have a regular and significant recovery trend through the whole process of the acupuncture intervention

Advanced bioelectrical signal processing methods: Past, present and future approach - Part III: Other biosignals

Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient digital signal processing methods are presented. This paper covers the following bioelectrical signals and their processing methods: electromyography (EMG), electroneurography (ENG), electrogastrography (EGG), electrooculography (EOG), electroretinography (ERG), and electrohysterography (EHG).Web of Science2118art. no. 606