High-Resolution Electrogastrogram: A Novel, Noninvasive Method for Determining Gastric Slow-Wave Direction and Speed

Early detection and intervention in diabetic gastroparesis: Role of body surface gastric mapping

Diabetic gastrointestinal neuropathy is a diabetes-related complication, associated with a complex interplay of hyperglycemic damage, autoimmune responses, oxidative stress, gastrointestinal hormones, and vascular insufficiency. Patients with diabetes should be monitored and therapeutic intervention introduced to prevent neuropathy due to diabetes prior to “the point of no return”. Determining gastric bioelectrical activity by body surface gastric mapping may be a promising option to monitor diabetic gastrointestinal neuropathy.

Surface mapping of gastric motor functions using MRI: a comparative study between humans and rats

The stomach's ability to store, mix, propel, and empty its content requires highly coordinated motor functions. However, current diagnostic tools cannot simultaneously assess these motor processes. This study aimed to use magnetic resonance imaging (MRI) to map multifaceted gastric motor functions, including accommodation, tonic and peristaltic contractions, and emptying, through a single noninvasive experiment for both humans and rats. Ten humans and 10 Sprague-Dawley rats consumed MRI-visible semisolid meals and underwent MRI scans. We used a surface model to analyze MRI data, capturing the deformation of the stomach wall on ingestion or during digestion. We inferred muscle activity, mapped motor processes, parcellated the stomach into functional regions, and revealed cross-species distinctions. In humans, both the fundus and antrum distended postmeal, followed by sustained tonic contractions to regulate intragastric pressure. Peristaltic contractions initiated from the distal fundus, including three concurrent wavefronts oscillating at 3.3 cycles/min and traveling at 1.7 to 2.9 mm/s. These motor functions facilitated linear gastric emptying with a 61-min half-time. In contrast, rats exhibited peristalsis from the midcorpus, showing two wavefronts oscillating at 5.0 cycles/min and traveling at 0.4 to 0.9 mm/s. For both species, motility features allowed functional parcellation of the stomach along a midcorpus division. This study maps region- and species-specific gastric motor functions. We demonstrate the value of MRI with surface modeling in understanding gastric physiology and its potential to become a new standard for clinical and preclinical investigations of gastric disorders at both individual and group levels.NEW & NOTEWORTHY A novel MRI technique can visualize how the stomach accommodates, mixes, and propels food for digestion in humans and animals alike. Digital models of gastric MRI reveal the functional maps, organization, and distinction of the stomach across individuals and species. This technique holds the unique potential to advance basic and clinical studies of functional gastric disorders.

Formation of Anisotropic Conducting Interlayer for High-Resolution Epidermal Electromyography Using Mixed-Conducting Particulate Composite

Epidermal electrophysiology is a non-invasive method used in research and clinical practices to study the electrical activity of the brain, heart, nerves, and muscles. However, electrode/tissue interlayer materials such as ionically conducting pastes can negatively affect recordings by introducing lateral electrode-to-electrode ionic crosstalk and reducing spatial resolution. To overcome this issue, biocompatible, anisotropic-conducting interlayer composites (ACI) that establish an electrically anisotropic interface with the skin are developed, enabling the application of dense cutaneous sensor arrays. High-density, conformable electrodes are also microfabricated that adhere to the ACI and follow the curvilinear surface of the skin. The results show that ACI significantly enhances the spatial resolution of epidermal electromyography (EMG) recording compared to conductive paste, permitting the acquisition of single muscle action potentials with distinct spatial profiles. The high-density EMG in developing mice, non-human primates, and humans is validated. Overall, high spatial-resolution epidermal electrophysiology enabled by ACI has the potential to advance clinical diagnostics of motor system disorders and enhance data quality for human-computer interface applications.

Vectorgastrogram: dynamic trajectory and recurrence quantification analysis to assess slow wave vector movement in healthy subjects

Functional gastric disorders entail chronic or recurrent symptoms, high prevalence and a significant financial burden. These disorders do not always involve structural abnormalities and since they cannot be diagnosed by routine procedures, electrogastrography (EGG) has been proposed as a diagnostic alternative. However, the method still has not been transferred to clinical practice due to the difficulty of identifying gastric activity because of the low-frequency interference caused by skin-electrode contact potential in obtaining spatiotemporal information by simple procedures. This work attempted to robustly identify the gastric slow wave (SW) main components by applying multivariate variational mode decomposition (MVMD) to the multichannel EGG. Another aim was to obtain the 2D SW vectorgastrogram VGGSW from 4 electrodes perpendicularly arranged in a T-shape and analyse its dynamic trajectory and recurrence quantification (RQA) to assess slow wave vector movement in healthy subjects. The results revealed that MVMD can reliably identify the gastric SW, with detection rates over 91% in fasting postprandial subjects and a frequency instability of less than 5.3%, statistically increasing its amplitude and frequency after ingestion. The VGGSW dynamic trajectory showed a statistically higher predominance of vertical displacement after ingestion. RQA metrics (recurrence ratio, average length, entropy, and trapping time) showed a postprandial statistical increase, suggesting that gastric SW became more intense and coordinated with a less complex VGGSW and higher periodicity. The results support the VGGSW as a simple technique that can provide relevant information on the "global" spatial pattern of gastric slow wave propagation that could help diagnose gastric pathologies.

A Low-Noise Low-Power 0.001Hz-1kHz Neural Recording System-on-Chip With Sample-Level Duty-Cycling

Advances in brain-machine interfaces and wearable biomedical sensors for healthcare and human-computer interactions call for precision electrophysiology to resolve a variety of biopotential signals across the body that cover a wide range of frequencies, from the mHz-range electrogastrogram (EGG) to the kHz-range electroneurogram (ENG). Existing integrated wearable solutions for minimally invasive biopotential recordings are limited in detection range and accuracy due to trade-offs in bandwidth, noise, input impedance, and power consumption. This article presents a 16-channel wide-band ultra-low-noise neural recording system-on-chip (SoC) fabricated in 65nm CMOS for chronic use in mobile healthcare settings that spans a bandwidth of 0.001 Hz to 1 kHz through a featured sample-level duty-cycling (SLDC) mode. Each recording channel is implemented by a delta-sigma analog-to-digital converter (ADC) achieving 1.0 μ V rms input-referred noise over 1Hz-1kHz bandwidth with a Noise Efficiency Factor (NEF) of 2.93 in continuous operation mode. In SLDC mode, the power supply is duty-cycled while maintaining consistently low input-referred noise levels at ultra-low frequencies (1.1 μV rms over 0.001Hz-1Hz) and 435 M Ω input impedance. The functionalities of the proposed SoC are validated with two human electrophysiology applications: recording low-amplitude electroencephalogram (EEG) through electrodes fixated on the forehead to monitor brain waves, and ultra-slow-wave electrogastrogram (EGG) through electrodes fixated on the abdomen to monitor digestion.

Application of electrogastrogram in assessment of gastric motility in acute pancreatitis

Background: Electrogastrogram (EGG) can reflect gastric motility disorders in many diseases, but its application in acute pancreatitis (AP) has not been studied. Therefore, our study aimed to investigate the value of EGG in assessing the existence of gastric motility disorder in patients with AP and in predicting the severity of AP. Methods: Patients with AP admitted to the First Affiliated Hospital of Nanchang University from June 2020 to December 2020 were enrolled. Five EGG parameters (Percentage of normal gastric slow wave (PNGSW), main frequency, average frequency, percentage of gastric tachycardia (PGT), percentage of gastric bradycardia (PGB)) were collected. The receiver operating characteristic (ROC) curve was constructed to judge the predictive value of EGG parameters to AP severity. Results: The PNGSW in AP patients was significantly lower than that of the control group (p < 0.05), and the PGB was higher in AP patients than that of the control group (p < 0.05). The area under curve (AUC) of the PNGSW and the PGB in diagnosing non-mild acute pancreatitis (N-MAP) were 0.777 (95% CI: 0.676-0.877, p < 0.001) and 0.775 (95% CI: 0.670-0.879, p < 0.001) respectively. After combining with C-reactive protein, the accuracy, sensitivity and specificity of predicting N-MAP were improved. Conclusion: EGG parameters can well reflect the gastric motility disorder of AP patients. The PNGSW and the PGB can be used to predict the occurrence of N-MAP.

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.

Electroanatomical mapping of the stomach with simultaneous biomagnetic measurements

Gastric motility is coordinated by bioelectric slow waves (SWs) and dysrhythmic SW activity has been linked with motility disorders. Magnetogastrography (MGG) is the non-invasive measurement of the biomagnetic fields generated by SWs. Dysrhythmia identification using MGG is currently challenging because source models are not well developed and the impact of anatomical variation is not well understood. A novel method for the quantitative spatial co-registration of serosal SW potentials, MGG, and geometric models of anatomical structures was developed and performed on two anesthetized pigs to verify feasibility. Electrode arrays were localized using electromagnetic transmitting coils. Coil localization error for the volume where the stomach is normally located under the sensor array was assessed in a benchtop experiment, and mean error was 4.2±2.3mm and 3.6±3.3° for a coil orientation parallel to the sensor array and 6.2±5.7mm and 4.5±7.0° for a perpendicular coil orientation. Stomach geometries were reconstructed by fitting a generic stomach to up to 19 localization coils, and SW activation maps were mapped onto the reconstructed geometries using the registered positions of 128 electrodes. Normal proximal-to-distal and ectopic SW propagation patterns were recorded from the serosa and compared against the simultaneous MGG measurements. Correlations between the center-of-gravity of normalized MGG and the mean position of SW activity on the serosa were 0.36 and 0.85 for the ectopic and normal propagation patterns along the proximal-distal stomach axis, respectively. This study presents the first feasible method for the spatial co-registration of MGG, serosal SW measurements, and subject-specific anatomy. This is a significant advancement because these data enable the development and validation of novel non-invasive gastric source characterization methods.

Stomach Geometry Reconstruction Using Serosal Transmitting Coils and Magnetic Source Localization

OBJECTIVE

Bioelectric slow waves (SWs) are a key regulator of gastrointestinal motility, and disordered SW activity has been linked to motility disorders. There is currently a lack of practical options for the acquisition of the 3D stomach geometry during research studies when medical imaging is challenging. Accurately recording the geometry of the stomach and co-registering electrode and sensor positions would provide context for in-vivo studies and aid the development of non-invasive methods of gastric SW assessment.

METHODS

A stomach geometry reconstruction method based on the localization of transmitting coils placed on the gastric serosa was developed. The positions and orientations of the coils, which represented boundary points and surface-normal vectors, were estimated using a magnetic source localization algorithm. Coil localization results were then used to generate surface models. The reconstruction method was evaluated against four 3D-printed anatomically realistic human stomach models and applied in a proof of concept in-vivo pig study.

RESULTS

Over ten repeated reconstructions, average Hausdorff distance and average surface-normal vector error values were 4.7 ±0.2 mm and 18.7 ±0.7° for the whole stomach, and 3.6 ±0.2 mm and 14.6 ±0.6° for the corpus. Furthermore, mean intra-array localization error was 1.4 ±1.1 mm for the benchtop experiment and 1.7 ±1.6 mm in-vivo.

CONCLUSION AND SIGNIFICANCE

Results demonstrated that the proposed reconstruction method is accurate and feasible. The stomach models generated by this method, when co-registered with electrode and sensor positions, could enable the investigation and validation of novel inverse analysis techniques.

Diagnostic Methods for Evaluation of Gastric Motility-A Mini Review

Gastric motility abnormalities are common in patients with disorders of gut-brain interaction, such as functional dyspepsia and gastroparesis. Accurate assessment of the gastric motility in these common disorders can help understand the underlying pathophysiology and guide effective treatment. A variety of clinically applicable diagnostic methods have been developed to objectively evaluate the presence of gastric dysmotility, including tests of gastric accommodation, antroduodenal motility, gastric emptying, and gastric myoelectrical activity. The aim of this mini review is to summarize the advances in clinically available diagnostic methods for evaluation of gastric motility and describe the advantages and disadvantages of each test.

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.

Endoscopic mucosal electrodes: New directions for recording and regulating gastric myoelectric activity

With the gradual deepening of the study of gastric motility disorders, people increasingly realize that gastric myoelectric activity plays an important role in coordinating gastric function. This article introduces the advantages of endoscopic mucosal electrodes compared with traditional electrodes. Several different types of mucosal electrodes and how to fix the electrodes by endoscope are introduced. Endoscopic mucosal electrodes can record and regulate gastric myoelectric activity, which has great value in the study of gastric motility. Endoscopic mucosal electrode technique refers to the fixation of the electrode in the designated part of the gastric mucosa by endoscope. Through endoscopic mucosal electrodes, on the one hand, we can record gastric myoelectric activity, on the other hand, we can carry out gastric electrical stimulation to interfere with gastric rhythm. Endoscopic mucosal electrodes have higher accuracy than traditional cutaneous electrodes, less trauma and lower cost than serosal electrodes. Endoscopic mucosal electrodes have a good application prospect for diseases such as gastroparesis and obesity.

Multichannel magnetogastrogram: a clinical marker for pediatric chronic nausea

Chronic nausea is a widespread functional disease in children with numerous comorbidities. High-resolution electrogastrogram (HR-EGG) has shown sufficient sensitivity as a noninvasive clinical marker to objectively detect distinct gastric slow wave properties in children with functional nausea. We hypothesized that the increased precision of magnetogastrogram (MGG) slow wave recordings could provide supplementary information not evident on HR-EGG. We evaluated simultaneous pre- and postprandial MGG and HR-EGG recordings in pediatric patients with chronic nausea and healthy asymptomatic subjects, while also measuring nausea intensity and nausea severity. We found significant reductions in postprandial dominant frequency and normogastric power, and higher levels of postprandial bradygastric power in patients with nausea in both MGG and HR-EGG. MGG also detected significantly lower preprandial normogastric power in patients. A significant difference in the mean preprandial gastric slow wave propagation direction was observed in patients as compared with controls in both MGG (control: 180 ± 61°, patient: 34 ±72°; P < 0.05) and HR-EGG (control: 240 ± 39°, patient: 180 ± 46°; P < 0.05). Patients also showed a significant change in the mean slow wave direction between pre- and postprandial periods in MGG (P < 0.05). No statistical differences were observed in propagation speed between healthy subjects and patients in either MGG or HR-EGG pre/postprandial periods. The use of MGG and/or HR-EGG represents an opportunity to assess noninvasively the effects of chronic nausea on gastric slow wave activity. MGG data may offer the opportunity for further refinement of the more portable and economical HR-EGG in future machine-learning approaches for functional nausea.NEW & NOTEWORTHY Pediatric chronic nausea is a difficult-to-measure subjective complaint that requires objective diagnosis, clinical assessment, and individualized treatment plans. Our study demonstrates that multichannel MGG used in conjunction with custom HR-EGG detects key pathological signatures of functional nausea in children. This quantifiable measure may allow more personalized diagnosis and treatment in addition to minimizing the cost and potential radiation associated with current diagnostic approaches.

Body surface gastric mapping to determine gastric motility patterns associated with delayed gastric emptying after pancreaticoduodenectomy. Gastric Electric Mapping after Pancreatoduodenectomy study protocol

INTRODUCTION

Delayed gastric emptying (DGE) is frequent after pancreaticoduodenectomy (PD). Although often associated with postoperative pancreatic fistula, the precise pathogenesis in patients with no underlying complications remains unclear. There is evidence to suggest that, after surgery, aberrant electrical pathways are formed in the stomach which could contribute to the development of DGE.Gastric Alimetry is a novel technology which measures the electrical activity of the stomach non-invasively using an array of electrodes applied to the skin of the abdomen. This technique, termed body surface gastric mapping (BSGM), has been validated in normal controls and in patients with functional dyspepsia syndromes. This study will investigate the efficacy and feasibility of using BSGM to assess gastric motility in patients who undergo PD.

METHODS AND ANALYSIS

This prospective cohort study will be conducted at a single large volume hepatobiliary unit in the UK. 50 patients who are planned to undergo PD will be included. BSGM measurement will be performed at four timepoints viz: preoperatively, day 4 postoperatively, at discharge and 6 months postoperatively. Key parameters of BSGM measurement, including wave amplitude, frequency and directional vector, will be measured at each timepoint and compared between different patient subgroups. Symptoms will be self-reported by patients during the recording using an iPad application designed for this purpose. Quality of life and patient experience will be assessed using standardised questionnaires at the end of the follow-up period.

ETHICS AND DISSEMINATION

The protocol has been approved by the research ethics committees of Newcastle University and the Health Research Authority (HRA) of the UK (ethical approval IRAS ID 305302). Findings will be published in peer-reviewed journals and presented at national and international conferences.

TRIAL REGISTRATION NUMBER

This study will automatically be registered with the ISRCTN registry by the HRA as part of the ethics approval process.

Simultaneous Gut-Brain Electrophysiology Shows Cognition and Satiety Specific Coupling

Recent studies, using high resolution magnetoencephalography (MEG) and electrogastrography (EGG), have shown that during resting state, rhythmic gastric physiological signals are linked with cortical brain oscillations. Yet, gut-brain coupling has not been investigated with electroencephalography (EEG) during cognitive brain engagement or during hunger-related gut engagement. In this study in 14 young adults (7 females, mean ± SD age 25.71 ± 8.32 years), we study gut-brain coupling using simultaneous EEG and EGG during hunger and satiety states measured in separate visits, and compare responses both while resting as well as during a cognitively demanding working memory task. We find that EGG-EEG phase-amplitude coupling (PAC) differs based on both satiety state and cognitive effort, with greater PAC modulation observed in the resting state relative to working memory. We find a significant interaction between gut satiation levels and cognitive states in the left fronto-central brain region, with larger cognitive demand based differences in the hunger state. Furthermore, strength of PAC correlated with behavioral performance during the working memory task. Altogether, these results highlight the role of gut-brain interactions in cognition and demonstrate the feasibility of these recordings using scalable sensors.

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.

Anatomically Constrained Gastric Slow Wave Localization using Biomagnetic Data

Detection of dysrhythmic gastric slow wave (SW) activity could have significant clinical utility because dysrhyth-mias have been linked to gastric motility disorders. The elec-trogastrogram (EGG) and magnetogastrogram (MGG) enable the non-invasive assessment of SW activity, but most analysis methods can only resolve frequency and velocity. Improved characterization of dysrhythmic propagation patterns from non-invasive measurements is important for the diagnosis of motility disorders and could allow early treatment stratification. In this study, we demonstrate the use of a penalized linear regression framework to localize SW events on the longitudinal stomach axis using simulated MGG data. Priors relating to spatial sparsity, the organization of wavefronts into complete circumferential rings, and the local distribution of depolar-ization and repolarization phases were used to constrain the inverse solution. This method was applied to MGG computed for a single wavefront case and a multiple wavefront case that were constructed from simulated 3 cycle-per-minute normal SW activity. Propagation patterns along the longitudinal stomach axis were identifiable from reconstructed SW activity for both cases. Localization error was 5.7 ± 0.1 mm and 7.7 ± 0.1 mm for each respective case within the distal stomach when the signal-to-noise ratio was 10 dB. Results indicate that penalized linear regression can successfully localize SW events provided the 3D geometry of the stomach and torso were acquired. Clinical Relevance- This method could help to improve the efficiency and accuracy of diagnosing gastric motility disorders from non-invasive measurements.

Clinical application and research progress of extracellular slow wave recording in the gastrointestinal tract

The physiological function of the gastrointestinal (GI) tract is based on the slow wave generated and transmitted by the interstitial cells of Cajal. Extracellular myoelectric recording techniques are often used to record the characteristics and propagation of slow wave and analyze the models of slow wave transmission under physiological and pathological conditions to further explore the mechanism of GI dysfunction. This article reviews the application and research progress of electromyography, bioelectromagnetic technology, and high-resolution mapping in animal and clinical experiments, summarizes the clinical application of GI electrical stimulation therapy, and reviews the electrophysiological research in the biliary system.

In vivo experimental validation of detection of gastric slow waves using a flexible multichannel electrogastrography sensor linear array

Background

Cutaneous electrogastrography (EGG) is a non-invasive technique that detects gastric bioelectrical slow waves, which in part govern the motility of the stomach. Changes in gastric slow waves have been associated with a number of functional gastric disorders, but to date accurate detection from the body-surface has been limited due to the low signal-to-noise ratio. The main aim of this study was to develop a flexible active-electrode EGG array. Methods: Two Texas Instruments CMOS operational amplifiers: OPA2325 and TLC272BID, were benchtop tested and embedded in a flexible linear array of EGG electrodes, which contained four recording electrodes at 20-mm intervals. The cutaneous EGG arrays were validated in ten weaner pigs using simultaneous body-surface and serosal recordings, using the Cyton biosensing board and ActiveTwo acquisition systems. The serosal recordings were taken using a passive electrode array via surgical access to the stomach. Signals were filtered and compared in terms of frequency, amplitude, and phase-shift based on the classification of propagation direction from the serosal recordings. Results: The data were compared over 709 cycles of slow waves, with both active cutaneous EGG arrays demonstrating comparable performance. There was an agreement between frequencies of the cutaneous EGG and serosal recordings (3.01 ± 0.03 vs 3.03 ± 0.05 cycles per minute; p = 0.75). The cutaneous EGG also demonstrated a reduction in amplitude during abnormal propagation of gastric slow waves (310 ± 50 µV vs 277 ± 9 µV; p < 0.01), while no change in phase-shift was observed (1.28 ± 0.09 s vs 1.40 ± 0.10 s; p = 0.36). Conclusion: A sparse linear cutaneous EGG array was capable of reliably detecting abnormalities of gastric slow waves. For more accurate characterization of gastric slow waves, a two-dimensional body-surface array will be required.

Perspective: A Framework for Addressing Dynamic Food Consumption Processes

The study of food consumption, diet, and related concepts is motivated by diverse goals, including understanding why food consumption impacts our health, and why we eat the foods we do. These varied motivations can make it challenging to define and measure consumption, as it can be specified across nearly infinite dimensions-from micronutrients to carbon footprint to food preparation. This challenge is amplified by the dynamic nature of food consumption processes, with the underlying phenomena of interest often based on the nature of repeated interactions with food occurring over time. This complexity underscores a need to not only improve how we measure food consumption but is also a call to support theoreticians in better specifying what, how, and why food consumption occurs as part of processes, as a prerequisite step to rigorous measurement. The purpose of this Perspective article is to offer a framework, the consumption process framework, as a tool that researchers in a theoretician role can use to support these more robust definitions of consumption processes. In doing so, the framework invites theoreticians to be a bridge between practitioners who wish to measure various aspects of food consumption and methodologists who can develop measurement protocols and technologies that can support measurement when consumption processes are clearly defined. In the paper we justify the need for such a framework, introduce the consumption process framework, illustrate the framework via a use case, and discuss existing technologies that enable the use of this framework and, by extension, more rigorous study of consumption. This consumption process framework demonstrates how theoreticians could fundamentally shift how food consumption is defined and measured towards more rigorous study of what, how, and why food is eaten as part of dynamic processes and a deeper understanding of linkages between behavior, food, and health.

Automated Machine Learning Pipeline Framework for Classification of Pediatric Functional Nausea Using High-resolution Electrogastrogram

OBJECTIVE

Pediatric functional nausea is challenging for patients to manage and for clinicians to treat since it lacks objective diagnosis and assessment. A data-driven non-invasive diagnostic screening tool that distinguishes the electro-pathophysiology of pediatric functional nausea from healthy controls would be an invaluable aid to support clinical decision-making in diagnosis and management of patient treatment methodology. The purpose of this paper is to present an innovative approach for objectively classifying pediatric functional nausea using cutaneous high-resolution electrogastrogram data.

METHODS

We present an Automated Electrogastrogram Data Analytics Pipeline framework and demonstrate its use in a 3x8 factorial design to identify an optimal classification model according to a defined objective function. Low-fidelity synthetic high-resolution electrogastrogram data were generated to validate outputs and determine SOBI-ICA noise reduction effectiveness.

RESULTS

A 10 parameter support vector machine binary classifier with a radial basis function was selected as the overall top-performing model from a pool of over 1000 alternatives via maximization of an objective function. This resulted in a 91.6% test ROC AUC score.

CONCLUSION

Using an automated machine learning pipeline approach to process high-resolution electrogastrogram data allows for clinically significant objective classification of pediatric functional nausea.

SIGNIFICANCE

To our knowledge, this is the first study to demonstrate clinically significant performance in the objective classification of pediatric nausea patients from healthy control subjects using experimental high-resolution electrogastrogram data. These results indicate a promising potential for high-resolution electrogastrography to serve as a data-driven screening tool for the objective diagnosis of pediatric functional nausea.

Reconstruction of stomach geometry using magnetic source localization

Routine diagnosis of gastric motility disorders represents a significant problem to current clinical practice. The non-invasive electrogastrogram (EGG) and magnetogastrogram (MGG) enable the assessment of gastric slow wave (SW) dysrhythmias that are associated with motility disorders. However, both modalities lack standardized methods for reliably detecting patterns of SW activity. Subject-specific anatomical information relating to the geometry of the stomach and its position within the torso have the potential to aid the development of relations between SWs and far-fields. In this study, we demonstrated the feasibility of using magnetic source localization to reconstruct the geometry of an anatomically realistic 3D stomach model. The magnetic fields produced by a small (6.35 × 6.35 mm) N35 neodymium magnet sequentially positioned at 64 positions were recorded by an array of 27 magnetometers. Finally, the magnetic dipole approximation and a particle swarm optimizer were used to estimate the position and orientation of the permanent magnet. Median position and orientation errors of 3.8 mm and 7.3° were achieved. The estimated positions were used to construct a surface mesh, and the Hausdorff Distance and Average Hausdorff Distance dissimilarity metrics for the reconstructed and ground-truth models were 11.6 mm and 2.4 mm, respectively. The results indicate that source localization using the magnetic dipole model can successfully reconstruct the geometry of the stomach.

Post-operative ileus: definitions, mechanisms and controversies

Post-operative ileus (POI) is a syndrome of impaired gastrointestinal transit which occurs following abdominal surgery. There are few effective targeted therapies for ileus, and research has been limited by inconsistent definitions and an incomplete understanding of the underlying pathophysiology. Despite considerable effort, there remains no widely-adopted definition of ileus, and recent work has identified variation in outcome reporting is a major source of heterogeneity in clinical trials. Outcomes should be clearly-defined, clinically-relevant, and reflective of the underlying biology, impacts on hospital resources and quality of life. Further collaborative efforts will be needed to develop consensus definitions and a core outcome set for postoperative gastrointestinal recovery. Investigation into the pathophysiology of POI has been hindered by use of low-resolution techniques and difficulties linking cellular mechanisms to dysmotility patterns and clinical symptoms. Recent evidence has suggested the common assumption of post-operative GI paralysis is incorrect, and that the distal colon becomes hyperactive following surgery. The post-operative inflammatory response is important in the pathophysiology of ileus, but the time course of this in humans remains unclear, with the majority of evidence coming from animal models. Future work should investigate dysmotility patterns underlying ileus, and identify biomarkers which may be used to diagnose, monitor and stratify patients with ileus.

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.

Quantification of Gastric Slow Wave Velocity using Bipolar High-Resolution Recordings

OBJECTIVE

Gastric bio-electrical slow waves are, in part, responsible for coordinating motility. High-resolution (HR) in vivo recordings can be used to capture the wavefront velocity of the propagating slow waves. A standard marking-and-grouping approach is typically employed along with manual review. Here, a bipolar velocity estimation (BVE) method was developed, which utilized local directional information to estimate the wavefront velocity in an efficient manner.

METHODS

With this approach, unipolar in vivo HR recordings were used to construct bipolar recordings in different directions. Then, the local directionality of the slow wave was extracted by calculating time delay information. The accuracy of the method was verified using synthetic data and then validated with in vivo HR pig experimental recordings.

RESULTS

Against ventilator noise amplitude of 0% - 70% of the average slow wave amplitude, the direction and speed error increased from 4.4 and 0.9 mm/s to 8.6 and 1.4 mm/s. For signals added with high-frequency noise with signal-to-noise ratios of 60 dB - 12 dB, the error increased from 8.0 and 1.0 mm/s to 9.8 and 1.2 mm/s. For experimental signals, the BVE algorithm resulted in 19.2 1.7 of direction error and 2.0 0.2 mm/s of speed error, when compared to the standard marking-and-grouping method.

CONCLUSION

Gastric slow wave wavefront velocities were estimated rapidly using the BVE algorithm with minimal errors.

SIGNIFICANCE

The BVE algorithm enables the ability to estimate wavefront velocities in HR recordings in an efficient manner.

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.

The effect of chronic nausea on gastric slow wave spatiotemporal dynamics in children

BACKGROUND

Chronic nausea in adolescents with functional gastrointestinal disorders is an increasingly reported but poorly understood symptom that negatively affects quality of life. Functional gastrointestinal disorders are known to correlate closely with slow wave rhythm disturbances. The ability to characterize gastric electrophysiologic perturbations in functional nausea patients could provide potential diagnostic and therapeutic tools for nausea patients.

METHODS

We used high-resolution electrogastrograms (HR-EGG) to measure gastric slow wave parameters in pediatric chronic nausea patients and healthy subjects both pre- and postprandial. We computed the dominant frequency, percentage power distribution, gastric slow wave propagation direction, and speed from HR-EGG.

KEY RESULTS

We observed significant differences in the dominant frequency and power distributed in normal and bradyarrhythmia frequency ranges when comparing patients and healthy subjects. Propagation patterns in healthy subjects were predominantly anterograde, while patients exhibited a variety of abnormalities including retrograde, anterograde, and disrupted patterns. There was a significant difference in the preprandial mean slow wave direction between healthy subjects (222° ± 22°) and patients (103° ± 66°; p ˂ 0.01), although the postprandial mean direction between healthy subjects and patients was similar (p = 0.73). No significant difference in slow wave propagation speed was found between patients and healthy subjects in either pre- (p = 0.21) or postprandial periods (p = 0.75).

CONCLUSIONS AND INFERENCES

The spatiotemporal characterization of gastric slow wave activity using HR-EGG distinguishes symptomatic chronic nausea patients from healthy subjects. This characterization may in turn inform and direct clinical decision-making and lead to further insight into its pathophysiology.

Gastric slow wave rhythm identification using new approach based on noise-assisted multivariate empirical mode decomposition and Hilbert-Huang transform

BACKGROUND

Electrogastrography (EGG) is the method of cutaneous recording of the myoelectrical activity of the stomach. A multi-channel signal is recorded non-invasively by means of electrodes placed outside the epigastric area. The normal electrical rhythm of the stomach (slow wave) may become significantly disturbed due to disorders of gastrointestinal tract. Abnormally fast electrical rhythms are termed tachygastria, while abnormally slow rhythms are known as bradygastria. Because some features of biological signals may go undetected using the classical methods of signal spectral analysis, we propose a new method for EGG rhythm identification.

METHODS

In this study, the calculation of the basic rhythms of multi-channel EGG signals is performed by means of the noise-assisted multivariate empirical mode decomposition (NA-MEMD) and Hilbert-Huang transform (HHT), using EGG data from eight healthy subjects. The results were compared with those obtained using classical spectral analysis.

KEY RESULTS

The mean values of the normogastric index for preprandial and two postprandial stages were found to be 64.78 ± 11.37%, 61.29 ± 15.86%, and 63.80 ± 13.24%, respectively. The obtained values of normogastric index are consistent with the normal human physiological value, which is approximately 70% for healthy subjects.

CONCLUSIONS

This method is able to capture features of the signal which are mostly undetectable by standard EGG processing methods. The EGG dominant rhythm identification using the instantaneous normogastric, bradygastric, and tachygastric indices provides new insights into biological EGG patterns.

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.

The influence of interstitial cells of Cajal loss and aging on slow wave conduction velocity in the human stomach

Loss of interstitial cells of Cajal (ICC) has been associated with gastric dysfunction and is also observed during normal aging at ~13% reduction per decade. The impact of ICC loss on gastric slow wave conduction velocity is currently undefined. This study correlated human gastric slow wave velocity with ICC loss and aging. High-resolution gastric slow wave mapping data were screened from a database of 42 patients with severe gastric dysfunction (n = 20) and controls (n = 22). Correlations were performed between corpus slow wave conduction parameters (frequency, velocity, and amplitude) and corpus ICC counts in patients, and with age in controls. Physiological parameters were further integrated into computational models of gastric mixing. Patients: ICC count demonstrated a negative correlation with slow wave velocity in the corpus (i.e., higher velocities with reduced ICC; r2  = .55; p = .03). ICC count did not correlate with extracellular slow wave amplitude (p = .12) or frequency (p = .84). Aging: Age was positively correlated with slow wave velocity in the corpus (range: 25-74 years; r2  = .32; p = .02). Age did not correlate with extracellular slow wave amplitude (p = .40) or frequency (p = .34). Computational simulations demonstrated that the gastric emptying rate would increase at higher slow wave velocities. ICC loss and aging are associated with a higher slow wave velocity. The reason for these relationships is unexplained and merit further investigation. Increased slow wave velocity may modulate gastric emptying higher, although in gastroparesis other pathological factors must dominate to prevent emptying.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate in vitro data, predict the in vivo performance, and ultimately support waivers of in vivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive in vivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as "PBPK absorption modeling" [Zhang et al. CPT: Pharmacometrics Syst. Pharmacol. 2017, 6, 492], "physiologically based absorption modeling", or "physiologically based biopharmaceutics modeling" (PBBM), remains rather low [Kesisoglou et al. J. Pharm. Sci. 2016, 105, 2723] [Heimbach et al. AAPS J. 2019, 21, 29]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, in vitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between in vitro, in silico, and in vivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive in vivo clinical studies.

Bioelectrical Signals for the Diagnosis and Therapy of Functional Gastrointestinal Disorders

Coordinated contractions and motility patterns unique to each gastrointestinal organ facilitate the digestive process. These motor activities are coordinated by bioelectrical events, sensory and motor nerves, and hormones. The motility problems in the gastrointestinal tract known as functional gastrointestinal disorders (FGIDs) are generally caused by impaired neuromuscular activity and are highly prevalent. Their diagnosis is challenging as symptoms are often vague and difficult to localize. Therefore, the underlying pathophysiological factors remain unknown. However, there is an increasing level of research and clinical evidence suggesting a link between FGIDs and altered bioelectrical activity. In addition, electroceuticals (bioelectrical therapies to treat diseases) have recently gained significant interest. This paper gives an overview of bioelectrical signatures of gastrointestinal organs with normal and/or impaired motility patterns and bioelectrical therapies that have been developed for treating FGIDs. The existing research evidence suggests that bioelectrical activities could potentially help to identify the diverse etiologies of FGIDs and overcome the drawbacks of the current clinically adapted methods. Moreover, electroceuticals could potentially be effective in the treatment of FGIDs and replace the limited existing conventional therapies which often attempt to treat the symptoms rather than the underlying condition.

Efficacy of gastric electrical stimulation in intractable nausea and vomiting at 10 years: A retrospective analysis of prospectively collected data

BACKGROUND

Gastric electrical simulation has been shown to relieve nausea and vomiting in medically refractory patients. Efficacy of gastric electrical stimulation has been reported mostly in short-term studies, but none has evaluated its efficacy beyond 10 years after implantation.

METHODS

Patients implanted at our center for medically refractory severe and chronic nausea and/or vomiting were evaluated before and over 10 years after implantation using symptomatic scale and quality of life (GIQLI) score. Improvement was defined as a reduction of more than 50% in vomiting frequency.

KEY RESULTS

A total of 50 patients were implanted from January 1998 to December 2009. Among them, 7 were explanted due to a lack of efficacy and/or side effects, 2 died, and 4 were lost to follow-up. Mean follow-up was 10.5 ± 3.7 years. In intention-to-treat analysis, 27/50 (54%) patients reported an improvement. Beyond 10 years, an improvement in early satiety (3.05 vs 1.76, <0.001), bloating (2.51 vs 1.70, P = .012), nausea (2.46 vs 1.35, P = .001), and vomiting (3.35 vs 1.49 P < .001) scores were observed. Quality of life improved over 10 years (GIQLI score: 69.7 vs. 86.4, P = .005) and body mass index (BMI: 23.4 vs. 26.2 kg/m² ; P = .048).

CONCLUSIONS AND INFERENCES

Gastric electrical simulation is effective in the long-term in patients with medically refractory nausea and vomiting, with an efficacy of 54% at 10 years on an intention-to-treat analysis. Other long-term observational studies are warranted to confirm these results.

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.

Hydrophilic Conductive Sponge Sensors for Fast Setup, Low Impedance Bio-potential Measurements

Low electrode-skin impedance can be achieved if the interface has an electrolytic medium that allows the movement of ions across the interface. Maintaining good physical contact of the sensor with the skin is imperative. We propose a novel hydrophilic conductive sponge interface that encapsulates both of these fundamental concepts into an effective physical realization. Our implementation uses a hydrophilic polyurethane prepolymer doped with conductive carbon nanofibers and cured to form a flexible sponge material that conforms to uneven surfaces, for instance, on parts of the scalp with hair. Our results show that our sponges are able to stay in a hydrated state with a low electrode-skin impedance of around 5kΩ for more than 20 hours. The novelty in our conductive sponges also lies in their versatility: the carbon nanofibers make the electrode effective even when the electrode dries up. The sensors remain conductive with a skin impedance on the order of 20kΩ when dry, which is substantially lower than typical impedance of dry electrodes, and are able to extract alpha wave EEG activity in both wet and dry conditions.

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).

Computational Reconstruction of 3D Stomach Geometry using Magnetic Field Source Localization

In this study, we investigated the feasibility of computationally reconstructing the 3D geometry of the stomach by performing source localization of the magnetic field (MF) induced from the stomach surface. Anatomically realistic stomach and torso models of a human participant, reconstructed from the CT images, were used in the computations. First, 128 coils with a radius of 5 mm were positioned on different locations on the stomach model. Next, MF at the sensor positions were computed using Bio-Savart law for the currents of 10 and 100 mA. Then, three noise levels were defined using the biomagnetic data recorded from the same participant and two additional sets of generated white-noise resulting in mean signal to noise ratios (SNR) of 20 and 10 dB. Finally, for each combination of the current and noise level, the magnetic dipole (MDP) approximation was performed to estimate coil positions. The performance of the source localization was assessed by computing the goodness of fit (GOF) values and the distance between the coil and the estimated MDP positions. We obtained GOF values over 98% for all coils and a mean localization error of 0.69±0.08 mm was achieved when 100 mA current was used to induce MF and only biomagnetic data was added. When additional white-noise was added, the GOF values decreased to 95% and the mean localization error increased to around 4 mm. A current of 10 mA was enough to localize the coil positions with a mean error around 8 mm even for the highest noise level we tested but for the few coils furthest from the body surface, the error was around 10 cm. The results indicate that source localization using the MDP approximation can successfully extract spatial information of the stomach.Clinical relevance-Extracting the spatial information of the stomach during the recording of the slow wave activity provides new insights in assessing gastric recordings and relating to disorders.

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.

Bayesian inverse methods for spatiotemporal characterization of gastric electrical activity from cutaneous multi-electrode recordings

Gastrointestinal (GI) problems give rise to 10 percent of initial patient visits to their physician. Although blockages and infections are easy to diagnose, more than half of GI disorders involve abnormal functioning of the GI tract, where diagnosis entails subjective symptom-based questionnaires or objective but invasive, intermittent procedures in specialized centers. Although common procedures capture motor aspects of gastric function, which do not correlate with symptoms or treatment response, recent findings with invasive electrical recordings show that spatiotemporal patterns of the gastric slow wave are associated with diagnosis, symptoms, and treatment response. We here consider developing non-invasive approaches to extract this information. Using CT scans from human subjects, we simulate normative and disordered gastric surface electrical activity along with associated abdominal activity. We employ Bayesian inference to solve the ill-posed inverse problem of estimating gastric surface activity from cutaneous recordings. We utilize a prior distribution on the spatiotemporal activity pertaining to sparsity in the number of wavefronts on the stomach surface, and smooth evolution of these wavefronts across time. We implement an efficient procedure to construct the Bayes optimal estimate and demonstrate its superiority compared to other commonly used inverse methods, for both normal and disordered gastric activity. Region-specific wave direction information is calculated and consistent with the simulated normative and disordered cases. We apply these methods to cutaneous multi-electrode recordings of two human subjects with the same clinical description of motor function, but different diagnosis of underlying cause. Our method finds statistically significant wave propagation in all stomach regions for both subjects, anterograde activity throughout for the subject with diabetic gastroparesis, and retrograde activity in some regions for the subject with idiopathic gastroparesis. These findings provide a further step towards towards non-invasive phenotyping of gastric function and indicate the long-term potential for enabling population health opportunities with objective GI assessment.

A Deep Convolutional Neural Network Approach to Classify Normal and Abnormal Gastric Slow Wave Initiation From the High Resolution Electrogastrogram

OBJECTIVE

Gastric slow wave abnormalities have been associated with gastric motility disorders. Invasive studies in humans have described normal and abnormal propagation of the slow wave. This study aims to disambiguate the abnormally functioning wave from one of normalcy using multi-electrode abdominal waveforms of the electrogastrogram (EGG).

METHODS

Human stomach and abdominal models are extracted from computed tomography scans. Normal and abnormal slow waves are simulated along stomach surfaces. Current dipoles at the stomachs surface are propagated to virtual electrodes on the abdomen with a forward model. We establish a deep convolutional neural network (CNN) framework to classify normal and abnormal slow waves from the multi-electrode waveforms. We investigate the effects of non-idealized measurements on performance, including shifted electrode array positioning, smaller array sizes, high body mass index (BMI), and low signal-to-noise ratio (SNR). We compare the performance of our deep CNN to a linear discriminant classifier using wave propagation spatial features.

RESULTS

A deep CNN framework demonstrated robust classification, with accuracy above 90% for all SNR above 0 dB, horizontal shifts within 3 cm, vertical shifts within 6 cm, and abdominal tissue depth within 6 cm. The linear discriminant classifier was much more vulnerable to SNR, electrode placement, and BMI.

CONCLUSION

This is the first study to attempt and, moreover, succeed in using a deep CNN to disambiguate normal and abnormal gastric slow wave patterns from high-resolution EGG data.

SIGNIFICANCE

These findings suggest that multi-electrode cutaneous abdominal recordings have the potential to serve as widely deployable clinical screening tools for gastrointestinal foregut disorders.

Bioelectronics for mapping gut activity

Gastric peristalsis is initiated and coordinated by an underlying bioelectrical activity, termed slow waves. High-resolution (HR) mapping of the slow waves has become a fundamental tool for accurately defining electrophysiological properties in gastroenterology, including dysrhythmias in gastric disorders such as gastroparesis and functional dyspepsia. Currently, HR mapping is achieved via acquisition of slow waves taken directly from the serosa of fasted subjects undergoing invasive abdominal surgery. Recently, a minimally invasive retractable catheter and electrode has been developed for HR mapping that can only be used in short-term studies in subjects undergoing laparoscopy. Noninvasive mapping has also emerged from multichannel cutaneous electrogastrography; however, it lacks sufficient resolution and is prone to artifacts. Bioelectronics that can map slow waves in conscious subjects, postprandially and long-term, are in high demand. Due to the low signal-to-noise ratio of cutaneous electrogastrography, electrodes for HR mapping of gut activity have to acquire slow waves directly from the gut; hence, development of novel device implantation methods has inevitably accompanied development of the devices themselves. Initial efforts that have paved the way toward achieving these goals have included development of miniature wireless systems with a limited number of acquisition channels using commercially available off-the-shelf electronic components, flexible HR electrodes, and endoscopic methods for minimally invasive device implantation. To further increase the spatial resolution of HR mapping, and to minimize the size and power consumption of the implant for long-term studies, application-specific integrated circuitry, wireless power transfer, and stretchable electronics technologies have had to be integrated into a single system.

Gastric Seed: Towards Distributed Ultrasonically Interrogated Millimeter-Sized Implants for Large-Scale Gastric Electrical-Wave Recording

This paper presents the concept of Gastric Seed, which is an ultrasonically interrogated millimeter-sized implant for gastric electrical-wave (also known as slow waves, SWs) recording. A network of Gastric Seeds can be endoscopically implanted within the stomach submucosal space for large-scale SW recording. This paper also summarizes our recent effort towards Gastric Seed development including ultrasonic self-regulated power management and addressable ultrasonic pulse-based data transfer. The proposed power management in the form of a voltage doubler only requires a single off-chip capacitor for simultaneous rectification, regulation and over-voltage protection (OVP) by utilizing ultrasonic transducer's internal capacitance and reverse current. For data transfer, sharp ultrasonic pulses are transmitted to reduce the implant's power consumption. A proof-of-concept addressable chip was fabricated in a 0.35-μm standard CMOS process. Utilizing two pairs of millimeter-sized stacked power/data ultrasonic transducers spaced by 3.75 cm in a water tank, the chip achieved measured regulated voltage of 3 V and data rate of 75 kbps with the data transmitter energy consumption of 440 pJ/bit.

Simple gastric motility assessment method with a single-channel electrogastrogram

Surface electrogastrography (EGG) is a non-invasive technique that is used to record myoelectrical activity of the stomach using cutaneous electrodes placed on the abdomen. Gastric motility assessment by EGG is a candidate for standard clinical procedure based on the quantification of parameters characteristic of gastric motility disorders. Despite its noticeable benefits, EGG is not widely implemented in clinical practice. The main reasons are: (1) lack of standardization of electrode placement, (2) time-consuming diagnostic procedures and (3) a complex multi-channel recording setup. We proposed a methodology in which an easy-to-use single-channel EGG, with a less time-consuming protocol (<1 h), would provide sufficient information for gastric motility assessment. Recordings from the three anatomical landmarks in 20 healthy young subjects were compared under two conditions, fasting and postprandial by evaluating the dominant frequency (DF). Our results showed that there is a statistically significant increase of DF after meal ingestion (p<0.05) in each of the three channels. However, when the study group was divided into two subgroups based on body mass index (BMI), the most appropriate recording location was above the body of the stomach (according to statistical significance p=7.82×10-6). We showed that a less time-consuming recording session with light meal intake could be used for the assessment of gastric myoelectrical activity (GMA).

An Algorithm for Automated, Noninvasive Detection of Cortical Spreading Depolarizations Based on EEG Simulations

OBJECTIVE

We present a novel signal processing algorithm for automated, noninvasive detection of cortical spreading depolarizations (CSDs) using electroencephalography (EEG) signals and validate the algorithm on simulated EEG signals. CSDs are waves of neurochemical changes that suppress the neuronal activity as they propagate across the brain's cortical surface. CSDs are believed to mediate secondary brain damage after brain trauma and cerebrovascular diseases like stroke. We address the following two key challenges in detecting CSDs from EEG signals: i) attenuation and loss of high spatial resolution information; and ii) cortical folds, which complicate tracking CSD waves.

METHODS

Our algorithm detects and tracks "wavefronts" of a CSD wave, and stitch together data across space and time to make a detection. To test our algorithm, we provide different models of CSD waves, including different widths of CSD suppressions and different patterns, and use them to simulate scalp EEG signals using head models of four subjects.

RESULTS AND CONCLUSION

Our results suggest that low-density EEG grids (40 electrodes) can detect CSD widths of 1.1 cm on average, while higher density EEG grids (340 electrodes) can detect CSD patterns as thin as 0.43 cm (less than minimum widths reported in prior works), among which single-gyrus CSDs are the hardest to detect because of their small suppression area.

SIGNIFICANCE

The proposed algorithm is a first step toward noninvasive, automated detection of CSDs, which can help in reducing secondary brain damages.