Artifact Rejection Methodology Enables Continuous, Noninvasive Measurement of Gastric Myoelectric Activity in Ambulatory Subjects. Sci Rep. 2018;8:5019. [PMID: 29568042 PMCID: PMC5864836 DOI: 10.1038/s41598-018-23302-9]

Correlation of electrogastrography and bioelectric impedance techniques for the gastric motility assessment

OBJECTIVES

The electrical bioimpedance (EBI) technique has been used to measure gastric motility and emptying parameters. A well-known technique for this purpose is electrogastrography (EGG). No correlation between EGG signal and mechanical motility has been reported. In this study, a direct data comparison of these two techniques was performed.

METHODS

23 volunteers underwent simultaneous gastric monitoring using EGG and EBI. Signal processing was performed to isolate the slow waves of 0.5-9 cpm. The parameters obtained from 70 % overlapped time slots of 3.5 min, included the dominant frequency and power of the normo-gastric region and the percentage of brady-, normo-, and tachy-gastric slow waves.

RESULTS

The EGG showed slightly higher values in dominant frequencies, whereas EBI displayed higher variability. High-frequency features were more significant in the EBI, with lower variability, and correlations were found in approximately half of the frequency spectra. Slow waves exhibited poor correlation, but were significant at 95 % of the timeslots.

CONCLUSIONS

Comparing EBI and EGG, global parameters in the normogastric region had slight variances, which may not significantly impact clinical findings. The sensitivity of the EBI to higher frequencies is evident.

Wearable Technology in Gastroenterology: Current Applications and Future Directions

Advances in wearable technology have revolutionized healthcare by enabling the continuous monitoring of patients and personalized healthcare delivery. In the field of gastroenterology, the integration of wearable devices and smartphone applications represents a promising frontier. As technology continues to expand, understanding the current landscape and future directions of wearable technology in gastroenterology is essential for improving patient outcomes and clinical practice. Background/Objectives: Most review articles, thus far, regarding wearable technology in healthcare have been directed towards cardiovascular health. The purpose of this review is to explore the evolving role of wearable technology in the management of gastrointestinal disorders, focusing on remote patient monitoring and the use of smartphone applications. Methods: We conducted a search for studies on wearable technology and included the following search terms: wearable technology, gastroenterology, wearable device, smartphone, application, heart rate variability, biosensor, watch, patch. We included randomized controlled trials, prospective studies, and feasibility studies published from 2018 onwards. We excluded studies in pediatrics or those unrelated to GI disorders. Results: We found that using wearable devices and digital health management may be an effective way to monitor symptoms, reduce hospitalizations, and improve healthcare delivery in several gastrointestinal diseases such as inflammatory bowel diseases, motility disorders, liver diseases, etc. Conclusions: This review proposes that remote patient monitoring through wearable devices and digital health management via smartphone applications could reduce hospitalizations and empower patients, though challenges related to data security, accuracy, and integration with the electronic medical record must be addressed.

[A New Paradigm in Diagnosing Functional Gastroduodenal Disorders: High-Resolution Electrogastrography]

High-resolution electrogastrography (HR-EGG) presents a new paradigm in diagnosing and treating functional gastroduodenal disorders. Unlike traditional electrogastrography, HR-EGG allows for a more precise analysis of the gastric electrical activity, offering improved diagnostic accuracy. Recent studies have revealed the clinical potential of HR-EGG, particularly in detecting abnormal electrical patterns in patients with functional dyspepsia and gastroparesis, supporting the development of novel therapeutic strategies. The non-invasive HR-EGG method has shown promise in identifying new biomarkers. Moreover, further integration of artificial intelligence, is expected to enhance diagnostic efficiency and develop more refined treatment models for functional gastrointestinal disorders.

Meal effects on gastric bioelectrical activity utilizing body surface gastric mapping in healthy subjects

BACKGROUND

Gastric sensorimotor disorders are prevalent. While gastric emptying measurements are commonly used, they may not fully capture the underlying pathophysiology. Body surface gastric mapping (BSGM) recently emerged to assess gastric sensorimotor dysfunction. This study assessed varying meal size on BSGM responses to inform test use in a wider variety of contexts.

METHODS

Data from multiple healthy cohorts receiving BSGM were pooled, using four different test meals. A standard BSGM protocol was employed: 30-min fasting, 4-h post-prandial, using Gastric Alimetry® (Alimetry, New Zealand). Meals comprised: (i) nutrient drink + oatmeal bar (482 kcal; 'standard meal'); (ii) oatmeal bar alone; egg and toast meal, and pancake (all ~250 kcal). Gastric Alimetry metrics included BMI-adjusted Amplitude, Principal Gastric Frequency, Gastric Alimetry Rhythm Index (GA-RI) and Fed:Fasted Amplitude Ratio (ff-AR).

KEY RESULTS

238 participants (59.2% female) were included. All meals significantly increased amplitude and frequency during the first postprandial hour (p < 0.05). There were no differences in postprandial frequency across meals (p > 0.05). The amplitude and GA-RI of the standard meal (n = 110) were significantly higher than the energy bar alone (n = 45) and egg meal (n = 65) (all p < 0.05). All BSGM metrics were comparable across the three smaller meals (p > 0.05). A higher symptom burden was found in the oatmeal bar group versus the standard meal and pancake meal (p = 0.01, 0.003, respectively).

CONCLUSIONS & INFERENCES

The consumption of lower calorie meals elicited different postprandial responses, when compared to the standard Gastric Alimetry meal. These data will guide interpretations of BSGM when applied with lower calorie meals.

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.

Systematic Review Registration

https://www.prisma-statement.org/.

A mutual information measure of phase-amplitude coupling using gamma generalized linear models

Introduction

Cross frequency coupling (CFC) between electrophysiological signals in the brain is a long-studied phenomenon and its abnormalities have been observed in conditions such as Parkinson's disease and epilepsy. More recently, CFC has been observed in stomach-brain electrophysiologic studies and thus becomes an enticing possible target for diseases involving aberrations of the gut-brain axis. However, current methods of detecting coupling, specifically phase-amplitude coupling (PAC), do not attempt to capture the phase and amplitude statistical relationships.

Methods

In this paper, we first demonstrate a method of modeling these joint statistics with a flexible parametric approach, where we model the conditional distribution of amplitude given phase using a gamma distributed generalized linear model (GLM) with a Fourier basis of regressors. We perform model selection with minimum description length (MDL) principle, demonstrate a method for assessing goodness-of-fit (GOF), and showcase the efficacy of this approach in multiple electroencephalography (EEG) datasets. Secondly, we showcase how we can utilize the mutual information, which operates on the joint distribution, as a canonical measure of coupling, as it is non-zero and non-negative if and only if the phase and amplitude are not statistically independent. In addition, we build off of previous work by Martinez-Cancino et al., and Voytek et al., and show that the information density, evaluated using our method along the given sample path, is a promising measure of time-resolved PAC.

Results

Using synthetically generated gut-brain coupled signals, we demonstrate that our method outperforms the existing gold-standard methods for detectable low-levels of phase-amplitude coupling through receiver operating characteristic (ROC) curve analysis. To validate our method, we test on invasive EEG recordings by generating comodulograms, and compare our method to the gold standard PAC measure, Modulation Index, demonstrating comparable performance in exploratory analysis. Furthermore, to showcase its use in joint gut-brain electrophysiology data, we generate topoplots of simultaneous high-density EEG and electrgastrography recordings and reproduce seminal work by Richter et al. that demonstrated the existence of gut-brain PAC. Using simulated data, we validate our method for different types of time-varying coupling and then demonstrate its performance to track time-varying PAC in sleep spindle EEG and mismatch negativity (MMN) datasets.

Conclusions

Our new measure of PAC using Gamma GLMs and mutual information demonstrates a promising new way to compute PAC values using the full joint distribution on amplitude and phase. Our measure outperforms the most common existing measures of PAC, and show promising results in identifying time varying PAC in electrophysiological datasets. In addition, we provide for using our method with multiple comparisons and show that our measure potentially has more statistical power in electrophysiologic recordings using simultaneous gut-brain datasets.

Effects of corticotropin-releasing hormone on gastric electrical activity and sensorimotor function in healthy volunteers: a double-blinded crossover study

Biopsychosocial factors are associated with disorders of gut-brain interaction (DGBI) and exacerbate gastrointestinal symptoms. The mechanisms underlying pathophysiological alterations of stress remain unclear. Corticotropin-releasing hormone (CRH) is a central regulator of the hormonal stress response and has diverse impact on different organ systems. The aim of the present study was to investigate the effects of peripheral CRH infusion on meal-related gastrointestinal symptoms, gastric electrical activity, and gastric sensorimotor function in healthy volunteers (HVs). In a randomized, double-blinded, placebo-controlled, crossover study, we evaluated the effects of CRH on gastric motility and sensitivity. HVs were randomized to receive either peripheral-administered CRH (100 µg bolus + 1 µg/kg/h) or placebo (saline), followed by at least a 7-day washout period and assignment to the opposite treatment. Tests encompassed saliva samples, gastric-emptying (GE) testing, body surface gastric mapping (BSGM, Gastric Alimetry; Alimetry) to assess gastric myoelectrical activity with real-time symptom profiling, and a gastric barostat study to assess gastric sensitivity to distention and accommodation. Twenty HVs [13 women, mean age 29.2 ± 5.3 yr, body mass index (BMI) 23.3 ± 3.8 kg/m2] completed GE tests, of which 18 also underwent BSGM measurements during the GE tests. The GE half-time decreased significantly after CRH exposure (65.2 ± 17.4 vs. 78.8 ± 24.5 min, P = 0.02) with significantly increased gastric amplitude [49.7 (34.7-55.6) vs. 31.7 (25.7-51.0) µV, P < 0.01], saliva cortisol levels, and postprandial symptom severity. Eleven HVs also underwent gastric barostat studies on a separate day. However, the thresholds for discomfort during isobaric distensions, gastric compliance, and accommodation did not differ between CRH and placebo.NEW & NOTEWORTHY In healthy volunteers, peripheral corticotropin-releasing hormone (CRH) infusion accelerates gastric-emptying rate and increases postprandial gastric response, accompanied by a rise in symptoms, but does not alter gastric sensitivity or meal-induced accommodation. These findings underscore a significant link between stress and dyspeptic symptoms, with CRH playing a pivotal role in mediating these effects.

Feasibility and repeatability of ultrasound-guided surface electroenterography to measure colonic slow wave motility in healthy adults

Surface electroenterography is a potential non-invasive alternative to current diagnostics of colonic motility disorders. However, electrode positioning in electroenterography is often based on general anatomy and may lack generalizability. Furthermore, the repeatability of electroenterography measurements is unknown. This study aimed to evaluate ultrasound-guided electrode positioning for electroenterography measurements and to determine the repeatability of those measurements. In ten healthy adults, two electroenterography procedures were performed, consisting of fasting, ultrasound-guided electrode localization and two 20-minute electroenterography recordings separated by a meal. The dominant frequency, the mean power density (magnitude of colonic motility) and the power percent difference (relative pre- to postprandial increase in magnitude) were determined. Repeatability was determined by Lin's concordance correlation coefficient. The results demonstrated that the dominant frequency did not differ between pre- and postprandial recordings and was 3 cpm, characteristic of colonic motility. The mean power density increased between the pre- and postprandial measurements, with an average difference of over 200%. The repeatability of both the dominant frequency and power density was poor to moderate, whereas the correlation coefficient of the power percent difference was poor. Concluding, ultrasound-guided surface electroenterography seems able to measure the gastrocolic reflex, but the dissatisfactory repeatability necessitates optimization of the measurement protocol.

Validation of body surface colonic mapping (BSCM) against high resolution colonic manometry for evaluation of colonic motility

Abnormal cyclic motor pattern (CMP) activity is implicated in colonic dysfunction, but the only tool to evaluate CMP activity, high-resolution colonic manometry (HRCM), remains expensive and not widely accessible. This study aimed to validate body surface colonic mapping (BSCM) through direct correlation with HRCM. Synchronous meal-test recordings were performed in asymptomatic participants with intact colons. A signal processing method for BSCM was developed to detect CMPs. Quantitative temporal analysis was performed comparing the meal responses and motility indices (MI). Spatial heat maps were also compared. Post-study questionnaires evaluated participants' preference and comfort/distress experienced from either test. 11 participants were recruited and 7 had successful synchronous recordings (5 females/2 males; median age: 50 years [range 38-63]). The best-correlating MI temporal analyses achieved a high degree of agreement (median Pearson correlation coefficient (Rp) value: 0.69; range 0.47-0.77). HRCM and BSCM meal response start and end times (Rp = 0.998 and 0.83; both p < 0.05) and durations (Rp = 0.85; p = 0.03) were similar. Heat maps demonstrated good spatial agreement. BSCM is the first non-invasive method to be validated by demonstrating a direct spatio-temporal correlation to manometry in evaluating colonic motility.

Emerging wearable technologies for multisystem monitoring and treatment of Parkinson's disease: a narrative review

Parkinson's disease (PD) is a chronic movement disorder characterized by a variety of motor and nonmotor comorbidities, including cognitive impairment, gastrointestinal (GI) dysfunction, and autonomic/sleep disturbances. Symptoms typically fluctuate with different settings and environmental factors and thus need to be consistently monitored. Current methods, however, rely on infrequent rating scales performed in clinic. The advent of wearable technologies presents a new avenue to track objective measures of PD comorbidities longitudinally and more frequently. This narrative review discusses and proposes emerging wearable technologies that can monitor manifestations of motor, cognitive, GI, and autonomic/sleep comorbidities throughout the daily lives of PD individuals. This can provide more wholistic insight into real-time physiological versus pathological function with the potential to better assess treatments during clinical trials and allow physicians to optimize treatment regimens. Additionally, this narrative review briefly examines novel applications of wearables as therapy for PD patients.

Comparing surface electroenterography measurements between patients suffering from Hirschsprung's disease and controls: a feasibility study

Current diagnostics in Hirschsprung's disease are often challenging and invasive. This study aims to investigate whether surface electroenterography can non-invasively discern healthy subjects from subjects suffering from Hirschsprung's disease. Nine healthy subjects (seven children, two adults) and eleven subjects suffering from surgically untreated Hirschsprung's disease (nine children, two adults) underwent an electroenterography procedure. This procedure consisted of ultrasound-guided placement of surface electrodes on the abdomen covering all parts of the colon, fasting and two 20-min electroenterography measurements separated by a meal. The dominant frequency, magnitude and relative increase (pre- to postprandial) of colonic activity were compared between both groups. The results showed that in the pediatric group, no significant differences in dominant frequency, colonic activity and relative power increase were observed between controls and patients. The adult patients showed decreased colonic motility and relative power increase in the electrodes closest to the distal colon, both when compared to the same electrodes in controls and to the more proximal electrodes of themselves. To conclude, electroenterography measurements in young children is challenging, but the results in adults demonstrate that these measurements can possibly distinguish between controls and Hirschsprung's patients. Therefore, optimization of electroenterography measurements in young children is necessary.

Gastric Alimetry Expands Patient Phenotyping in Gastroduodenal Disorders Compared with Gastric Emptying Scintigraphy

INTRODUCTION

Gastric emptying testing (GET) assesses gastric motility, however, is nonspecific and insensitive for neuromuscular disorders. Gastric Alimetry (GA) is a new medical device combining noninvasive gastric electrophysiological mapping and validated symptom profiling. This study assessed patient-specific phenotyping using GA compared with GET.

METHODS

Patients with chronic gastroduodenal symptoms underwent simultaneous GET and GA, comprising a 30-minute baseline, 99m TC-labelled egg meal, and 4-hour postprandial recording. Results were referenced to normative ranges. Symptoms were profiled in the validated GA App and phenotyped using rule-based criteria based on their relationships to the meal and gastric activity: (i) sensorimotor, (ii) continuous, and (iii) other.

RESULTS

Seventy-five patients were assessed, 77% female. Motility abnormality detection rates were as follows: GET 22.7% (14 delayed, 3 rapid), GA spectral analysis 33.3% (14 low rhythm stability/low amplitude, 5 high amplitude, and 6 abnormal frequency), and combined yield 42.7%. In patients with normal spectral analysis, GA symptom phenotypes included sensorimotor 17% (where symptoms strongly paired with gastric amplitude, median r = 0.61), continuous 30%, and other 53%. GA phenotypes showed superior correlations with Gastroparesis Cardinal Symptom Index, Patient Assessment of Upper Gastrointestinal Symptom Severity Index, and anxiety scales, whereas Rome IV Criteria did not correlate with psychometric scores ( P > 0.05). Delayed emptying was not predictive of specific GA phenotypes.

DISCUSSION

GA improves patient phenotyping in chronic gastroduodenal disorders in the presence and absence of motility abnormalities with increased correlation with symptoms and psychometrics compared with gastric emptying status and Rome IV criteria. These findings have implications for the diagnostic profiling and personalized management of gastroduodenal disorders.

Exploring the Gut-Brain Connection in Gastroparesis With Autonomic and Gastric Myoelectric Monitoring

OBJECTIVE

The goal of this study was to identify autonomic and gastric myoelectric biomarkers from throughout the day that differentiate patients with gastroparesis, diabetics without gastroparesis, and healthy controls, while providing insight into etiology.

METHODS

We collected 19 24-hour recordings of electrocardiogram (ECG) and electrogastrogram (EGG) data from healthy controls and patients with diabetic or idiopathic gastroparesis. We used physiologically and statistically rigorous models to extract autonomic and gastric myoelectric information from the ECG and EGG data, respectively. From these, we constructed quantitative indices which differentiated the distinct groups and demonstrated their application in automatic classification paradigms and as quantitative summary scores.

RESULTS

We identified several differentiators that separate healthy controls from gastroparetic patient groups, specifically around sleep and meals. We also demonstrated the downstream utility of these differentiators in automatic classification and quantitative scoring paradigms. Even with this small pilot dataset, automated classifiers achieved an accuracy of 79% separating autonomic phenotypes and 65% separating gastrointestinal phenotypes. We also achieved 89% accuracy separating controls from gastroparetic patients in general and 90% accuracy separating diabetics with and without gastroparesis. These differentiators also suggested varying etiologies for different phenotypes.

CONCLUSION

The differentiators we identified were able to successfully distinguish between several autonomic and gastrointestinal (GI) phenotypes using data collected while at-home with non-invasive sensors.

SIGNIFICANCE

Autonomic and gastric myoelectric differentiators, obtained using at-home recording of fully non-invasive signals, can be the first step towards dynamic quantitative markers to track severity, disease progression, and treatment response for combined autonomic and GI phenotypes.

Gastric Alimetry® Test Interpretation in Gastroduodenal Disorders: Review and Recommendations

Chronic gastroduodenal symptoms are prevalent worldwide, and there is a need for new diagnostic and treatment approaches. Several overlapping processes may contribute to these symptoms, including gastric dysmotility, hypersensitivity, gut-brain axis disorders, gastric outflow resistance, and duodenal inflammation. Gastric Alimetry® (Alimetry, New Zealand) is a non-invasive test for evaluating gastric function that combines body surface gastric mapping (high-resolution electrophysiology) with validated symptom profiling. Together, these complementary data streams enable important new clinical insights into gastric disorders and their symptom correlations, with emerging therapeutic implications. A comprehensive database has been established, currently comprising > 2000 Gastric Alimetry tests, including both controls and patients with various gastroduodenal disorders. From studies employing this database, this paper presents a systematic methodology for Gastric Alimetry test interpretation, together with an extensive supporting literature review. Reporting is grouped into four sections: Test Quality, Spectral Analysis, Symptoms, and Conclusions. This review compiles, assesses, and evaluates each of these aspects of test assessment, with discussion of relevant evidence, example cases, limitations, and areas for future work. The resultant interpretation methodology is recommended for use in clinical practice and research to assist clinicians in their use of Gastric Alimetry as a diagnostic aid and is expected to continue to evolve with further development.

Reliability and validity of brain-gastric phase synchronization

Recent studies have reported that various brain regions, mainly sensory, unimodal regions, display phase synchronization with the stomach's slow (0.05 Hz) myoelectrical rhythm. These gastric-brain interactions have broad implications, from feeding behavior to functional gastrointestinal disorders. However, in contrast to other interoceptive signals (e.g., heart rate) and their relation to the brain, little is known about the reliability of these gastric-brain interactions, their robustness to artifacts such as motion, and whether they can be generalized to new samples. Here we examined these aspects in 43 subjects that had undergone multiple runs of concurrent electrogastrography (EGG), brain fMRI, and pulse oximetry. We also repeated all analyses in an open dataset of a highly sampled individual. We found a set of brain regions that were coupled with the EGG signal after controlling for non-grey matter (GM) signals, head motion, and cardiac artifacts. These regions exhibited significant overlap with previous work. However, we also showed that prior to confound regression, the spatial extent of the gastric network was largely overestimated. Finally, we found substantial test-retest reliability in both the brain and the gastric signals when estimated alone, but not for measures of gastric-brain synchrony. Together, these results provide methodological scaffolding for future research into brain-stomach interactions and for a better understanding of the role of the gastric network.

Principles and clinical methods of body surface gastric mapping: Technical review

BACKGROUND AND PURPOSE

Chronic gastric symptoms are common, however differentiating specific contributing mechanisms in individual patients remains challenging. Abnormal gastric motility is present in a significant subgroup, but reliable methods for assessing gastric motor function in clinical practice are lacking. Body surface gastric mapping (BSGM) is a new diagnostic aid, employs multi-electrode arrays to measure and map gastric myoelectrical activity non-invasively in high resolution. Clinical adoption of BSGM is currently expanding following studies demonstrating the ability to achieve specific patient subgrouping, and subsequent regulatory clearances. An international working group was formed in order to standardize clinical BSGM methods, encompassing a technical group developing BSGM methods and a clinical advisory group. The working group performed a technical literature review and synthesis focusing on the rationale, principles, methods, and clinical applications of BSGM, with secondary review by the clinical group. The principles and validation of BSGM were evaluated, including key advances achieved over legacy electrogastrography (EGG). Methods for BSGM were reviewed, including device design considerations, patient preparation, test conduct, and data processing steps. Recent advances in BSGM test metrics and reference intervals are discussed, including four novel metrics, being the 'principal gastric frequency', BMI-adjusted amplitude, Gastric Alimetry Rhythm Index™, and fed: fasted amplitude ratio. An additional essential element of BSGM has been the introduction of validated digital tools for standardized symptom profiling, performed simultaneously during testing. Specific phenotypes identifiable by BSGM and the associated symptom profiles were codified with reference to pathophysiology. Finally, knowledge gaps and priority areas for future BSGM research were also identified by the working group.

Comparison of Gastric Alimetry® body surface gastric mapping versus electrogastrography spectral analysis

Electrogastrography (EGG) non-invasively evaluates gastric motility but is viewed as lacking clinical utility. Gastric Alimetry® is a new diagnostic test that combines high-resolution body surface gastric mapping (BSGM) with validated symptom profiling, with the goal of overcoming EGG's limitations. This study directly compared EGG and BSGM to define performance differences in spectral analysis. Comparisons between Gastric Alimetry BSGM and EGG were conducted by protocolized retrospective evaluation of 178 subjects [110 controls; 68 nausea and vomiting (NVS) and/or type 1 diabetes (T1D)]. Comparisons followed standard methodologies for each test (pre-processing, post-processing, analysis), with statistical evaluations for group-level differences, symptom correlations, and patient-level classifications. BSGM showed substantially tighter frequency ranges vs EGG in controls. Both tests detected rhythm instability in NVS, but EGG showed opposite frequency effects in T1D. BSGM showed an 8× increase in the number of significant correlations with symptoms. BSGM accuracy for patient-level classification was 0.78 for patients vs controls and 0.96 as compared to blinded consensus panel; EGG accuracy was 0.54 and 0.43. EGG detected group-level differences in patients, but lacked symptom correlations and showed poor accuracy for patient-level classification, explaining EGG's limited clinical utility. BSGM demonstrated substantial performance improvements across all domains.

Defining and Phenotyping Gastric Abnormalities in Long-Term Type 1 Diabetes Using a Novel Body Surface Gastric Mapping Device

Background and Aims

Diabetic gastroenteropathy is associated with poor glycemic control and morbidity in people with type 1 diabetes (T1D). There is a lack of noninvasive techniques to assess and monitor gastric abnormalities. We aimed to define phenotypes of gastric myoelectrical abnormalities in people with longstanding T1D with and without symptoms using a novel noninvasive body surface gastric mapping (BSGM) device.

Methods

BSGM was performed on people with T1D of >10 years duration and matched controls, employing Gastric Alimetry (Alimetry, New Zealand), comprising of a high-resolution 64-channel array, validated symptom-logging App, and wearable reader.

Results

Thirty-two people with T1D were recruited (15 with a high symptom burden), and 32 controls. Those with symptoms showed more unstable gastric myoelectrical activity (Gastric Alimetry Rhythm Index 0.39 vs 0.51, P = .017; and lower average spatial covariance 0.48 vs 0.51, P = .009) compared with controls. Symptomatic patients also had a higher prevalence of peripheral neuropathy (67% vs 6%, P = .001), anxiety/depression diagnoses (27% vs 0%, P = .001), and higher mean hemoglobin A1C levels (76 vs 56 mmol/mol, P < .001). BSGM defined distinct phenotypes in T1D participants including those with markedly unstable gastric rhythms (4/32, 12.5%) and abnormally high gastric frequencies (9/32, 28%). Deviation in gastric frequency was positively correlated with symptoms of bloating, upper gut pain, nausea and vomiting, and fullness (R > 0.35, P < .05).

Conclusion

Gastric symptoms in people with longstanding T1D correlate with myoelectrical abnormalities on BSGM evaluation, in addition to glycemic control, psychological comorbidities, and peripheral neuropathy. BSGM using Gastric Alimetry identified a range of myoelectrical phenotypes, presenting targets for diagnosis, monitoring, and therapy.

Exploring the aperiodic nature of parasympathetic activity during sleep in idiopathic gastroparesis

The parasympathetic nervous system is necessary to regulate both sleep and digestion. Investigating abnormalities during the controlled setting of sleep can shed light on digestion, specifically for patients with idiopathic gastroparesis. In this study, we specifically investigate heartbeat-derived parasympathetic activity during sleep at very low frequencies, relevant to sleep cycle regulation. To do this, we adapt a method that extracts both periodic and aperiodic information from the power spectral density and recognize that the aperiodic activity may contain information relevant to very low frequencies. After testing on both synthetic noise data (pink and white) and overnight data from seven healthy controls and idiopathic gastroparetics, we find that the healthy controls' low-frequency aperiodic activity reflects pink noise structure, while the majority of the patients' aperiodic activity reflects white noise structure. At these low frequencies, these differences suggest differences in autonomic sleep cycle regulation.Clinical Relevance- This methodology can be optimized to track the health of the parasympathetic nervous system and suggest whether individual disease etiology is autonomic-related.

Dynamic Monitoring of Probiotics Effect in Parkinson's Disease Patients via Swarm Decomposition and Bispectral Analysis of Electrogastrograms

People with Parkinson's Disease (PwP) experience a significant deterioration of their daily life quality due to non-motor symptoms, with gastrointestinal dysfunctions manifesting as a vanguard of the latter. Electrogastrography (EGG) is a noninvasive diagnostic tool that can potentially provide biomarkers for the monitoring of dynamic gastric alterations that are related to daily lifestyle and treatment regimens. In this work, a robust analysis of EGG dynamics is introduced to evaluate the effect of probiotic treatment on PwP. The proposed framework, namely biSEGG, introduces a Swarm Decomposition-based enhancement of the EGG, combined with Bispectral feature engineering to model the underlying Quadratic Phase Coupling interactions between the gastric activity oscillatory components of EGG. The biSEGG features are benchmarked against the conventional Power Spectrum-based ones and evaluated through machine learning classifiers. The experimental results, when biSEGG was applied on data epochs from 11 PwP (probiotic vs placebo, AUROC: 0.67, Sensitivity/Specificity: 75/58%), indicate the superiority of biSEGG over Power Spectrum-based approaches and justify the efficiency of biSEGG in capturing and explaining intervention- and meal consumption-related alterations of the gastric activity in PwP.Clinical relevance- biSEGG holds potential for dynamic monitoring of gastrointestinal dysfunction and health status of PwP across diverse daily life scenarios.

Normative Values for Body Surface Gastric Mapping Evaluations of Gastric Motility Using Gastric Alimetry: Spectral Analysis

INTRODUCTION

Body surface gastric mapping (BSGM) is a new noninvasive test of gastric function. BSGM offers several novel and improved biomarkers of gastric function capable of differentiating patients with overlapping symptom profiles. The aim of this study was to define normative reference intervals for BSGM spectral metrics in a population of healthy controls.

METHODS

BSGM was performed in healthy controls using Gastric Alimetry (Alimetry, New Zealand) comprising a stretchable high-resolution array (8 × 8 electrodes; 196 cm 2 ), wearable Reader, and validated symptom-logging App. The evaluation encompassed a fasting baseline (30 minutes), 482 kCal meal, and 4-hour postprandial recording. Normative reference intervals were calculated for BSGM metrics including the Principal Gastric Frequency, Gastric Alimetry Rhythm Index (a measure of the concentration of power in the gastric frequency band over time), body mass index (BMI)-adjusted amplitude (μV), and fed:fasted amplitude ratio. Data were reported as median and reference interval (5th and/or 95th percentiles).

RESULTS

A total of 110 subjects (55% female, median age 32 years [interquartile range 24-50], median BMI 23.8 kg/m 2 [interquartile range 21.4-26.9]) were included. The median Principal Gastric Frequency was 3.04 cycles per minute; reference interval: 2.65-3.35 cycles per minute. The median Gastric Alimetry Rhythm Index was 0.50; reference interval: ≥0.25. The median BMI-adjusted amplitude was 37.6 μV; reference interval: 20-70 μV. The median fed:fasted amplitude ratio was 1.85; reference interval ≥1.08. A higher BMI was associated with a shorter meal-response duration ( P = 0.014).

DISCUSSION

This study provides normative reference intervals for BSGM spectral data to inform diagnostic interpretations of abnormal gastric function.

Gastric Alimetry ® improves patient phenotyping in gastroduodenal disorders compared to gastric emptying scintigraphy alone

Objectives

Gastric emptying testing (GET) assesses gastric motility, however is non-specific and insensitive for neuromuscular disorders. Gastric Alimetry® (GA) is a new medical device combining non-invasive gastric electrophysiological mapping and validated symptom profiling. This study assessed patient-specific phenotyping using GA compared to GET.

Methods

Patients with chronic gastroduodenal symptoms underwent simultaneous GET and GA, comprising a 30-minute baseline, 99m TC-labelled egg meal, and 4-hour postprandial recording. Results were referenced to normative ranges. Symptoms were profiled in the validated GA App and phenotyped using rule-based criteria based on their relationships to the meal and gastric activity: i) sensorimotor; ii) continuous; and iii) other.

Results

75 patients were assessed; 77% female. Motility abnormality detection rates were: GET 22.7% (14 delayed, 3 rapid); GA spectral analysis 33.3% (14 low rhythm stability / low amplitude; 5 high amplitude; 6 abnormal frequency); combined yield 42.7%. In patients with normal spectral analysis, GA symptom phenotypes included: sensorimotor 17% (where symptoms strongly paired with gastric amplitude; median r=0.61); continuous 30%; other 53%. GA phenotypes showed superior correlations with GCSI, PAGI-SYM, and anxiety scales, whereas Rome IV Criteria did not correlate with psychometric scores (p>0.05). Delayed emptying was not predictive of specific GA phenotypes.

Conclusions

GA improves patient phenotyping in chronic gastroduodenal disorders in the presence and absence of motility abnormalities with improved correlation with symptoms and psychometrics compared to gastric emptying status and Rome IV criteria. These findings have implications for the diagnostic profiling and personalized management of gastroduodenal disorders.

Study Highlights

1) WHAT IS KNOWN Chronic gastroduodenal symptoms are common, costly and greatly impact on quality of lifeThere is a poor correlation between gastric emptying testing (GET) and symptomsGastric Alimetry® is a new medical device combining non-invasive gastric electrophysiological mapping and validated symptom profiling 2) WHAT IS NEW HERE Gastric Alimetry generates a 1.5x higher yield for motility abnormalities than GETWith symptom profiling, Gastric Alimetry identified 2.7x more specific patient categories than GETGastric Alimetry improves clinical phenotyping, with improved correlation with symptoms and psychometrics compared to GET.

Gut-Brain Coupling and Multilevel Physiological Response to Biofeedback Relaxation After a Stressful Task Under Virtual Reality Immersion: A Pilot Study

Human physiological reactions to the environment are coordinated by the interactions between brain and viscera. In particular, the brain, heart, and gastrointestinal tract coordinate with each other to provide physiological equilibrium by involving the central, autonomic, and enteric nervous systems. Recent studies have demonstrated an electrophysiological coupling between the gastrointestinal tract and the brain (gut-brain axis) under resting-state conditions. As the gut-brain axis plays a key role in individual stress regulation, we aimed to examine modulation of gut-brain coupling through the use of an overwhelming and a relaxing module as a first step toward modeling of the underlying mechanisms. This study was performed in 12 participants who, under a virtual reality environment, performed a 9-min cognitive stressful task followed by a 9-min period of relaxation. Brain activity was captured by electroencephalography, autonomic activities by photoplethysmography, and electrodermal and gastric activities by electrogastrography. Results showed that compared with the stressful task, relaxation induced a significant decrease in both tonic and phasic sympathetic activity, with an increase in brain alpha power and a decrease in delta power. The intensity of gut-brain coupling, as assessed by the modulation index of the phase-amplitude coupling between the normogastric slow waves and the brain alpha waves, decreased under the relaxation relative to the stress condition. These results highlight the modulatory effect of biofeedback relaxation on gut-brain coupling and suggest noninvasive multilevel electrophysiology as a promising way to investigate the mechanisms underlying gut-brain coupling in physiological and pathological situations.

Location-aware ingestible microdevices for wireless monitoring of gastrointestinal dynamics

Localization and tracking of ingestible microdevices in the gastrointestinal (GI) tract is valuable for the diagnosis and treatment of GI disorders. Such systems require a large field-of-view of tracking, high spatiotemporal resolution, wirelessly operated microdevices and a non-obstructive field generator that is safe to use in practical settings. However, the capabilities of current systems remain limited. Here, we report three dimensional (3D) localization and tracking of wireless ingestible microdevices in the GI tract of large animals in real time and with millimetre-scale resolution. This is achieved by generating 3D magnetic field gradients in the GI field-of-view using high-efficiency planar electromagnetic coils that encode each spatial point with a distinct magnetic field magnitude. The field magnitude is measured and transmitted by the miniaturized, low-power and wireless microdevices to decode their location as they travel through the GI tract. This system could be useful for quantitative assessment of the GI transit-time, precision targeting of therapeutic interventions and minimally invasive procedures.

A novel scalable electrode array and system for non-invasively assessing gastric function using flexible electronics

BACKGROUND

Disorders of gastric function are highly prevalent, but diagnosis often remains symptom-based and inconclusive. Body surface gastric mapping is an emerging diagnostic solution, but current approaches lack scalability and are cumbersome and clinically impractical. We present a novel scalable system for non-invasively mapping gastric electrophysiology in high-resolution (HR) at the body surface.

METHODS

The system comprises a custom-designed stretchable high-resolution "peel-and-stick" sensor array (8 × 8 pre-gelled Ag/AgCl electrodes at 2 cm spacing; area 225 cm² ), wearable data logger with custom electronics incorporating bioamplifier chips, accelerometer and Bluetooth synchronized in real-time to an App with cloud connectivity. Automated algorithms filter and extract HR biomarkers including propagation (phase) mapping. The system was tested in a cohort of 24 healthy subjects to define reliability and characterize features of normal gastric activity (30 m fasting, standardized meal, and 4 h postprandial).

KEY RESULTS

Gastric mapping was successfully achieved non-invasively in all cases (16 male; 8 female; aged 20-73 years; BMI 24.2 ± 3.5). In all subjects, gastric electrophysiology and meal responses were successfully captured and quantified non-invasively (mean frequency 2.9 ± 0.3 cycles per minute; peak amplitude at mean 60 m postprandially with return to baseline in <4 h). Spatiotemporal mapping showed regular and consistent wave activity of mean direction 182.7° ± 73 (74.7% antegrade, 7.8% retrograde, 17.5% indeterminate).

CONCLUSIONS AND INFERENCES

BSGM is a new diagnostic tool for assessing gastric function that is scalable and ready for clinical applications, offering several biomarkers that are improved or new to gastroenterology practice.

Comparison of Dry and Wet Electrodes for Detecting Gastrointestinal Activity Patterns from Body Surface Electrical Recordings

Gastrointestinal motility patterns can be mapped via electrical signals measured non-invasively on the body surface. However, short-term (≈ 2-4 h) meal response studies as well as long-term monitoring (≥ 24 h) may be hindered by skin irritation inherent with traditional Ag/AgCl pre-gelled ("wet") electrodes. The aim of this work was to investigate the practical utility of using dry electrodes for GI body-surface electrical measurements. To directly compare dry vs. wet electrodes, we simultaneously recorded electrical signals from both types arranged in a 9-electrode array during an ≈ 2.5 h colonic meal-response study. Wavelet-based analyses were used to identify the signature post-meal colonic cyclic motor patterns. Blinded comparison of signal quality was carried out by four expert manual reviewers in order to assess the practical utility of each electrode type for identifying GI activity patterns. Dry electrodes recorded high-quality GI signals with signal-to-noise ratio of 10.0 ± 3.5 dB, comparable to that of wet electrodes (9.9 ± 3.6 dB). Although users rated dry electrodes as slightly more difficult to self-apply, they caused no skin irritation and were thus better tolerated overall. Dry electrodes are a more comfortable alternative to conventional wet electrode systems, and may offer a potentially viable option for long-term GI monitoring studies.

An automated artifact detection and rejection system for body surface gastric mapping

BACKGROUND

Body surface gastric mapping (BSGM) is a new clinical tool for gastric motility diagnostics, providing high-resolution data on gastric myoelectrical activity. Artifact contamination was a key challenge to reliable test interpretation in traditional electrogastrography. This study aimed to introduce and validate an automated artifact detection and rejection system for clinical BSGM applications.

METHODS

Ten patients with chronic gastric symptoms generated a variety of artifacts according to a standardized protocol (176 recordings) using a commercial BSGM system (Alimetry, New Zealand). An automated artifact detection and rejection algorithm was developed, and its performance was compared with a reference standard comprising consensus labeling by 3 analysis experts, followed by comparison with 6 clinicians (3 untrained and 3 trained in artifact detection). Inter-rater reliability was calculated using Fleiss' kappa.

KEY RESULTS

Inter-rater reliability was 0.84 (95% CI:0.77-0.90) among experts, 0.76 (95% CI:0.68-0.83) among untrained clinicians, and 0.71 (95% CI:0.62-0.79) among trained clinicians. The sensitivity and specificity of the algorithm against experts was 96% (95% CI:91%-100%) and 95% (95% CI:90%-99%), respectively, vs 77% (95% CI:68%-85%) and 99% (95% CI:96%-100%) against untrained clinicians, and 97% (95% CI:92%-100%) and 88% (95% CI:82%-94%) against trained clinicians.

CONCLUSIONS & INFERENCES

An automated artifact detection and rejection algorithm was developed showing &gt;95% sensitivity and specificity vs expert markers. This algorithm overcomes an important challenge in the clinical translation of BSGM and is now being routinely implemented in patient test interpretations.

Validation of noninvasive body-surface gastric mapping for detecting gastric slow-wave spatiotemporal features by simultaneous serosal mapping in porcine

Gastric disorders are increasingly prevalent, but reliable noninvasive tools to objectively assess gastric function are lacking. Body-surface gastric mapping (BSGM) is a noninvasive method for the detection of gastric electrophysiological features, which are correlated with symptoms in patients with gastroparesis and functional dyspepsia. Previous studies have validated the relationship between serosal and cutaneous recordings from limited number of channels. This study aimed to comprehensively evaluate the basis of BSGM from 64 cutaneous channels and reliably identify spatial biomarkers associated with slow-wave dysrhythmias. High-resolution electrode arrays were placed to simultaneously capture slow waves from the gastric serosa (32 × 6 electrodes at 4 mm spacing) and epigastrium (8 × 8 electrodes at 20 mm spacing) in 14 porcine subjects. BSGM signals were processed based on a combination of wavelet and phase information analyses. A total of 1,185 individual cycles of slow waves were assessed, out of which 897 (76%) were classified as normal antegrade waves, occurring in 10 (71%) subjects studied. BSGM accurately detected the underlying slow wave in terms of frequency (r = 0.99, P = 0.43) as well as the direction of propagation (P = 0.41, F-measure: 0.92). In addition, the cycle-by-cycle match between BSGM and transitions of gastric slow wave dysrhythmias was demonstrated. These results validate BSGM as a suitable method for noninvasively and accurately detecting gastric slow-wave spatiotemporal profiles from the body surface.NEW & NOTEWORTHY Gastric dysfunctions are associated with abnormalities in the gastric bioelectrical slow waves. Noninvasive detection of gastric slow waves from the body surface can be achieved through multichannel, high-resolution, body-surface gastric mapping (BSGM). BSGM matched the spatiotemporal characteristics of gastric slow waves recorded directly and simultaneously from the serosal surface of the stomach. Abnormal gastric slow waves, such as retrograde propagation, ectopic pacemaker, and colliding wavefronts can be detected by changes in the phase of BSGM.

Gastric dysfunction in patients with chronic nausea and vomiting syndromes defined by a noninvasive gastric mapping device

Chronic nausea and vomiting syndromes (NVSs) are prevalent and debilitating disorders. Putative mechanisms include gastric neuromuscular disease and dysregulation of brain-gut interaction, but clinical tests for objectively defining gastric motor function are lacking. A medical device enabling noninvasive body surface gastric mapping (BSGM) was developed and applied to evaluate NVS pathophysiology. BSGM was performed in 43 patients with NVS and 43 matched controls using Gastric Alimetry (Alimetry), a conformable high-resolution array (8 × 8 electrodes; 20-mm interelectrode spacing), wearable reader, and validated symptom-logging app. Continuous measurement encompassed a fasting baseline (30 minutes), 482-kilocalorie meal, and 4-hour postprandial recording, followed by spectral and spatial biomarker analyses. Meal responses were impaired in NVS, with reduced amplitudes compared to controls (median, 23.3 microvolts versus 38.0 microvolts, P < 0.001), impaired fed-fasting power ratios (1.1 versus 1.6, P = 0.02), and disorganized slow waves (spatial frequency stability, 13.6 versus 49.5; P < 0.001). Two distinct NVS subgroups were evident with indistinguishable symptoms (all P > 0.05). Most patients (62%) had normal BSGM studies with increased psychological comorbidities (43.5% versus 7.7%; P = 0.03) and anxiety scores (median, 16.5 versus 13.0; P = 0.035). A smaller subgroup (31%) had markedly abnormal BSGM, with biomarkers correlating with symptoms (nausea, pain, excessive fullness, early satiety, and bloating; all r > 0.35, P < 0.05). Patients with NVS share overlapping symptoms but comprise distinct underlying phenotypes as revealed by a BSGM device. These phenotypes correlate with symptoms, which should inform clinical management and therapeutic trial design.

Automated classification of sleep and wake from single day triaxial accelerometer data

Actigraphy allows for the remote monitoring of subjects' activity for clinical and research purposes. However, most standard methods are built for proprietary measures from specific devices that are not widely used. In this study, we develop an algorithm for classifying sleep and awake using a single day of triaxial accelerometer data, which can be acquired from all smart devices. This algorithm consists of two stages, clustering and hidden Markov modeling, and outperforms standard algorithms in sensitivity (94%), specificity (93 %), and overall accuracy (93%) across seven subjects. This method can help automate actigraphy analyses at scale using widely available technology using even a single day's worth of data. Clinical Relevance- Automated monitoring of patients' activity at home can help track recovery trajectories after surgery and injury, disease progression, treatment response.

Machine Learning for Healthcare Wearable Devices: The Big Picture

Using artificial intelligence and machine learning techniques in healthcare applications has been actively researched over the last few years. It holds promising opportunities as it is used to track human activities and vital signs using wearable devices and assist in diseases' diagnosis, and it can play a great role in elderly care and patient's health monitoring and diagnostics. With the great technological advances in medical sensors and miniaturization of electronic chips in the recent five years, more applications are being researched and developed for wearable devices. Despite the remarkable growth of using smart watches and other wearable devices, a few of these massive research efforts for machine learning applications have found their way to market. In this study, a review of the different areas of the recent machine learning research for healthcare wearable devices is presented. Different challenges facing machine learning applications on wearable devices are discussed. Potential solutions from the literature are presented, and areas open for improvement and further research are highlighted.

Implementing Digital Technologies in Clinical Trials: Lessons Learned

Multiple digital health technologies have been evaluated across clinical development programs, including external, wearable, implantable, and ingestible devices and sensors, along with digital mobile health applications (apps) that are accessible via users' personal electronic devices (e.g., smartphones, tablets, and computers). Several of these technologies have been incorporated into our ongoing neurology and respiratory clinical development programs. Based on our experience, one of the greatest potential benefits of digital health technologies is the ability to collect objective and/or biological data continuously or at regular intervals outside of office visits during a patient's normal daily activities to provide additional efficacy and safety information, versus data capture from traditional episodic, time point-based office visits. Many challenges encountered with digital health technologies can be successfully addressed by providing the appropriate training to staff and patients, ensuring availability of appropriate infrastructure support, and conducting pilot studies before scaling up to larger trials. Overall, our experience with digital health technologies demonstrated their potential to increase the amount of objective data collected in clinical trials, expand patient access to trials, and facilitate further improvement of clinical outcomes.

The gastric conduction system in health and disease: a translational review

Gastric peristalsis is critically dependent on an underlying electrical conduction system. Recent years have witnessed substantial progress in clarifying the operations of this system, including its pacemaking units, its cellular architecture, and slow-wave propagation patterns. Advanced techniques have been developed for assessing its functions at high spatiotemporal resolutions. This review synthesizes and evaluates this progress, with a focus on human and translational physiology. A current conception of the initiation and conduction of slow-wave activity in the human stomach is provided first, followed by a detailed discussion of its organization at the cellular and tissue level. Particular emphasis is then given to how gastric electrical disorders may contribute to disease states. Gastric dysfunction continues to grow in their prevalence and impact, and while gastric dysrhythmia is established as a clear and pervasive feature in several major gastric disorders, its role in explaining pathophysiology and informing therapy is still emerging. New insights from high-resolution gastric mapping are evaluated, together with historical data from electrogastrography, and the physiological relevance of emerging biomarkers from body surface mapping such as retrograde propagating slow waves. Knowledge gaps requiring further physiological research are highlighted.

A High-Precision, Low-Cost, Wireless, Multi-Channel Electrogastrography System

Electrogastrography (EGG), a method of recording gastric electrical activity, is attractive in both research and clinical applications because of its noninvasive nature. However, the commercially available wireless EGG acquisition system is relatively expensive and the portability is poor. The internal circuit design is unknown, making it difficult to further adjust the system. To overcome these limitations, we have developed a multi-channel EGG acquisition system based on the idea of "low magnification and wide dynamic range". In the system, an analog front end (AFE) including preamplifier, right leg drive (RLD) and low-pass anti-aliasing filter is designed according to the characteristics of the EGG signal, and the high-precision analog-to-digital converter (ADC) is selected for EGG signal collection. The system has the advantages of high precision, low noise, low power consumption, low cost, and high portability. The wireless multi-channel EGG acquisition system can achieve the characteristics of portability and device miniaturization. We provide multiple differential channels for acquisition, which will be helpful to obtain more information about gastric slow wave propagation and coupling.

Effects of anatomical variations of the stomach on body-surface gastric mapping investigated using a large population-based multiscale simulation approach

The contractions of the stomach are governed by bioelectrical slow waves that can be detected non-invasively from the body-surface. Diagnosis of gastric motility disorders remains challenging due to the limited information provided by symptoms and tests, including standard electrogastrography (EGG). Body-surface gastric mapping (BSGM) is a novel technique that measures the resultant body-surface potentials using an array of multiple cutaneous electrodes. However, there is no established protocol to guide the placement of the mapping array and to account for the effects of biodiversity on the interpretation of gastric BSGM data. This study aims to quantify the effect of anatomical variation of the stomach on body surface potentials. To this end, 93 subject specific models of the stomach and torso were developed. Anatomical models were developed based on data obtained from the Cancer Imaging Archive. For each subject a set of points were created to model general anatomy the stomach and the torso, using a finite element mesh. A bidomain model was used to simulate the gastric slow waves in the antegrade wave (AW) direction and formation of colliding waves (CW). The resultant dipole was calculated, and a forward modeling approach was employed to simulate body-surface potentials. Simulated data were sampled from a 55 array of electrodes from the body-surface and compared between AW and CW cases. Anatomical parameters such as the Euclidean distance from the xiphoid process (8.6 2.2 cm), orientation relative to the axial plane (195 20.0) were quantified. Electrophysiological simulations of AW and CW were both correlated to specific metrics derived from BSGM signals. In general, the maximum amplitude () and orientation () of the signals provided consistent separation of AW and CW. The findings of this study will aid gastric BSGM electrode array design and placement protocol in clinical practices.

Miniaturized wireless gastric pacing via inductive power transfer with non-invasive monitoring using cutaneous Electrogastrography

BACKGROUND

Gastroparesis is a debilitating disease that is often refractory to pharmacotherapy. While gastric electrical stimulation has been studied as a potential treatment, current devices are limited by surgical complications and an incomplete understanding of the mechanism by which electrical stimulation affects physiology.

METHODS

A leadless inductively-powered pacemaker was implanted on the gastric serosa in an anesthetized pig. Wireless pacing was performed at transmitter-to-receiver distances up to 20 mm, frequency of 0.05 Hz, and pulse width of 400 ms. Electrogastrogram (EGG) recordings using cutaneous and serosal electrode arrays were analyzed to compute spectral and spatial statistical parameters associated with the slow wave.

RESULTS

Our data demonstrated evident change in EGG signal patterns upon initiation of pacing. A buffer period was noted before a pattern of entrainment appeared with consistent and low variability in slow wave direction. A spectral power increase in the EGG frequency band during entrainment also suggested that pacing increased strength of the slow wave.

CONCLUSION

Our preliminary in vivo study using wireless pacing and concurrent EGG recording established the foundations for a minimally invasive approach to understand and optimize the effect of pacing on gastric motor activity as a means to treat conditions of gastric dysmotility.

Diabetes Technology Meeting 2020

Diabetes Technology Society hosted its annual Diabetes Technology Meeting on November 12 to November 14, 2020. This meeting brought together speakers to cover various perspectives about the field of diabetes technology. The meeting topics included artificial intelligence, digital health, telemedicine, glucose monitoring, regulatory trends, metrics for expressing glycemia, pharmaceuticals, automated insulin delivery systems, novel insulins, metrics for diabetes monitoring, and discriminatory aspects of diabetes technology. A live demonstration was presented.

Emerging wearable technology applications in gastroenterology: A review of the literature

The field of gastroenterology has recently seen a surge in wearable technology to monitor physical activity, sleep quality, pain, and even gut activity. The past decade has seen the emergence of wearable devices including Fitbit, Apple Watch, AbStats, and ingestible sensors. In this review, we discuss current and future devices designed to measure sweat biomarkers, steps taken, sleep efficiency, gastric electrical activity, stomach pH, and intestinal contents. We also summarize several clinical studies to better understand wearable devices so that we may assess their potential benefit in improving healthcare while also weighing the challenges that must be addressed.

Body surface mapping of the stomach: New directions for clinically evaluating gastric electrical activity

BACKGROUND

Gastric motility disorders, which include both functional and organic etiologies, are highly prevalent. However, there remains a critical lack of objective biomarkers to guide efficient diagnostics and personalized therapies. Bioelectrical activity plays a fundamental role in coordinating gastric function and has been investigated as a contributing mechanism to gastric dysmotility and sensory dysfunction for a century. However, conventional electrogastrography (EGG) has not achieved common clinical adoption due to its perceived limited diagnostic capability and inability to impact clinical care. The last decade has seen the emergence of novel high-resolution methods for invasively mapping human gastric electrical activity in health and disease, providing important new insights into gastric physiology. The limitations of EGG have also now become clearer, including the finding that slow-wave frequency alone is not a reliable discriminator of gastric dysrhythmia, shifting focus instead toward altered spatial patterns. Recently, advances in bioinstrumentation, signal processing, and computational modeling have aligned to allow non-invasive body surface mapping of the stomach to detect spatiotemporal gastric dysrhythmias. The clinical relevance of this emerging strategy to improve diagnostics now awaits determination.

PURPOSE

This review evaluates these recent advances in clinical gastric electrophysiology, together with promising emerging data suggesting that novel gastric electrical signatures recorded at the body surface (termed "body surface mapping") may correlate with symptoms. Further technological progress and validation data are now awaited to determine whether these advances will deliver on the promise of clinical gastric electrophysiology diagnostics.

Robust Methods to Detect Abnormal Initiation in the Gastric Slow Wave from Cutaneous Recordings

Upper gastrointestinal (GI) disorders are highly prevalent, with gastroparesis (GP) and functional dyspepsia (FD) affecting 3% and 10% of the US population, respectively. Despite overlapping symptoms, differing etiologies of GP and FD have distinct optimal treatments, thus making their management a challenge. One such cause, that of gastric slow wave abnormalities, affects the electromechanical coordination of pacemaker cells and smooth muscle cells in propelling food through the GI tract. Abnormalities in gastric slow wave initiation location and propagation patterns can be treated with novel pacing technologies but are challenging to identify with traditional spectral analyses from cutaneous recordings due to their occurrence at the normal slow wave frequency. This work advances our previous work in developing a 3D convolutional neural network to process multi-electrode cutaneous recordings and successfully classify, in silico, normal versus abnormal slow wave location and propagation patterns. Here, we use transfer learning to build a method that is robust to heterogeneity in both the location of the abnormal initiation on the stomach surface as well as the recording start times with respect to slow wave cycles. We find that by starting with training lowest-complexity models and building complexity in training sets, transfer learning one model to the next, the final network exhibits, on average, 80% classification accuracy in all but the most challenging spatial abnormality location, and below 5% Type-I error probabilities across all locations.

Electrogastrography for psychophysiological research: Practical considerations, analysis pipeline, and normative data in a large sample

Electrogastrography (EGG) is the noninvasive electrophysiological technique used to record gastric electrical activity by means of cutaneous electrodes placed on the abdomen. EGG has been so far mostly used in clinical studies in gastroenterology, but it represents an attractive method to study brain-viscera interactions in psychophysiology. Compared to the literature on electrocardiography for instance, where practical recommendations and normative data are abundant, the literature on EGG in humans remains scarce. The aim of this article is threefold. First, we review the existing literature on the physiological basis of the EGG, pathways of brain-stomach interactions, and experimental findings in the cognitive neuroscience and psychophysiology literature. We then describe practical issues faced when recording the EGG in young healthy participants, from data acquisition to data analysis, and propose a semi-automated analysis pipeline together with associated MATLAB code. The analysis pipeline aims at identifying a regular rhythm that can be safely attributed to the stomach, through multiple steps. Finally, we apply these recording and analysis procedures in a large sample (N = 117) of healthy young adult male and female participants in a moderate (<5 hr) to prolonged (>10 hr) fasting state to establish the normative distribution of several EGG parameters. Our results are overall congruent with the clinical gastroenterology literature, but suggest using an electrode coverage extending to lower abdominal locations than current clinical guidelines. Our results indicate a marginal difference in EGG peak frequency between male and female participants, and that the gastric rhythm becomes more irregular after prolonged fasting.

Open-source 128-channel bioamplifier module for ambulatory monitoring of gastrointestinal electrical activity

We present an open-source, low-cost, portable, 128-channel bioamplifier module designed specifically for ambulatory, long-term (≥24 hr) monitoring of gastrointestinal (GI) electrical activity. The electronics hardware integrates stateof-the-art, commercial-off-the-shelf components on a custom PCB. Features include on-board data logging, wireless data streaming, subject motion monitoring, and stable operation up to the maximum 2 kHz/channel sampling rate tested. The new device operates for ≈ 30 hr continuously powered by a single 3.7 V, 2500 mAh LiPo battery. The 3D-printed ABS mechanical enclosure is robust and small (13.1 × 8.8 × 2.5 cm), so that the device can be carried in a standard Holter monitor pouch. Results from initial 128-channel, high spatial resolution body surface colon mapping experiments demonstrate the utility of this new device for GI applications. The new bioamplifier module could also be used for multichannel recording experiments in a variety of biomedical domains to study electrical activity patterns of the neuromuscular system (EMG), uterus (EHG), heart (ECG), and brain (EEG).

Gut-Brain Computer Interfacing (GBCI) : Wearable Monitoring of Gastric Myoelectric Activity

We propose a new area for wearable technology and interaction by acquiring gastrointestinal signals non-invasively from the abdomen. The mind-gut connection has flourished as a research area in the past two decades, elucidating the guts key role in stress, affect, and memory. Meanwhile, engineering advancements have shown potential in accuracy of non-invasive gastric recordings. Here, we investigate the design and specification of a wearable system for the recording of gut-brain activity non-invasively. We also present results from a preliminary pilot test of a wearable gut-brain computer interface (GBCI).

Spatial Patterns From High-Resolution Electrogastrography Correlate With Severity of Symptoms in Patients With Functional Dyspepsia and Gastroparesis

BACKGROUND & AIMS

Invasive gastric electrical mapping has revealed spatial abnormalities of the slow wave in subjects with gastroparesis and functional gastrointestinal disorders. Cutaneous high-resolution electrogastrography (HR-EGG) is a non-invasive method that can detect spatial features of the gastric slow wave. We performed HR-EGG in subjects with active foregut symptoms to evaluate associations between gastric myoelectric abnormalities, symptoms (based on a validated questionnaire), and gastric emptying.

METHODS

We performed a case-control study of 32 subjects, including 7 healthy individuals (controls), 7 subjects with functional dyspepsia and normal gastric emptying, and 18 subjects with gastroparesis, from a tertiary care program. All subjects were assessed by computed tomography imaging of the abdomen and HR-EGG and completed the PAGI-SYM questionnaire on foregut symptoms, which includes the gastroparesis cardinal symptom index. We performed volume reconstruction of the torso and stomach from computed tomography images to guide accurate placement of the HR-EGG array.

RESULTS

Spatial slow-wave abnormalities were detected in 44% of subjects with foregut symptoms. Moreover, subjects with a higher percentage of slow waves with aberrant propagation direction had a higher total gastroparesis cardinal symptom index score (r = 0.56; P < .001) and more severe abdominal pain (r = 0.46; P = .009). We found no correlation between symptoms and traditional EGG parameters.

CONCLUSIONS

In case-control study, we found that the genesis of symptoms of functional dyspepsia and gastroparesis is likely multifactorial, including possible contribution from gastric myoelectric dysfunction. Abnormal spatial parameters, detected by cutaneous HR-EGG, correlated with severity of upper gastrointestinal symptoms, regardless of gastric emptying. This noninvasive, repeatable approach might be used to identify patients for whom gastric myoelectric dysfunction contributes to functional dyspepsia and gastroparesis.