Mapping slow waves and spikes in chronically instrumented conscious dogs: automated on-line electrogram analysis

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.

Design and Application of an Inflatable Cuff to Aid High-Resolution Intestinal Slow Wave Recordings. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020;2020:3953-3956. [PMID: 33018865 DOI: 10.1109/embc44109.2020.9175219]

Intestinal motility is coordinated by myogenic, neuronal and hormonal factors. Myogenic control of motility via bioelectric slow waves (SW) has been investigated using low-resolution and high-resolution (HR) electrical mapping techniques. Due to the highly conformable and irregular surface of the gut, suboptimal coverage of HR recordings may occur. In this study we designed and developed an inflatable cuff as a platform to apply even pressure across the intestinal surface to achieve consistent and reliable recordings. The inflatable cuff and a HR electrode array were applied in vivo to demonstrate the reliability of SW signal acquisition over a range of inflatable pressures (0 - 5 mm Hg). The frequency, amplitude, percentage of viable signals and signal to noise ratio metrics of the SW signals were computed and compared. Overall, with an increase in inflatable pressure from 0 to 5 mm Hg, the frequency did not change, but the amplitude of the SWs decreased from 0.10 to 0.07 mV. The noise levels were consistent across the range of inflatable pressure levels and the percentage of viable SW recordings improved significantly from 57% to 74% after application of 1 mm Hg of pressure. The inflatable and conformable cuff presented in this study provides a reliable platform for HR mapping of bioelectrical events in the intestines and other conformable organs.Clinical Relevance- This framework improves the quality and reliability of bioelectrical high-resolution recordings obtained from the small intestine. In the future, these recordings will improve our understanding of the pathophysiological mechanisms governing intestinal motility disorders and may provide clinicians with new strategies for diagnosis and treatment.

Detection of Monophasic Slow-wave Activation Phase Using Wavelet Decomposition

Gastric bio-electric slow-waves are in part responsible for generating motility. Extracellular recordings of the slow-wave activation phase have yielded significant physiological insight about its spatio-temporal characteristics. With the growth of multi-electrode data and long recording periods, there is a need for automated methods to detect the activation phase in a reliable and accurate manner. In this study, the Variable Threshold Wavelet (VTW) algorithm was developed, featuring wavelet decomposition, to compute the derivative to detect the slow-wave activation phase of monophasic signals. The performance of the VTW algorithm was compared against an existing Falling-Edge, Variable Threshold (FEVT) algorithm. Varying levels of synthetic noise representing ventilator and high-frequency noise were added to in vivo slow-wave recordings. Sensitivity, positive-predictive value, area under the curve (A_roc) metric and percentage improvement metric (PIM) of activation phase identification accuracy were calculated. Compared to the existing FEVT algorithm, the VTW algorithm achieved similar performance in identifying the activation phase of slow-waves with various levels of ventilator noise. In the presence of high-frequency noise, the VTW algorithm improved the A_roc of the existing FEVT algorithm by 11.1%. The VTW algorithm can now be applied to analyze normal and abnormal slow-wave recordings.

A Framework for Spatiotemporal Analysis of Gastrointestinal Spike Burst Propagation

Gastrointestinal spike bursts are a bioelectrical phenomenon associated with motility. These events when initiated propagate a small distance and abruptly terminate activating a small area defined as a patch. Understanding normal and abnormal propagation patterns of these events may shed light on the root causes of functional motility disorders. This study develops an automated framework for spatiotemporal analysis of spike bursts. High-resolution electrical signals were obtained from the pig intestine, after which intestinal spike bursts were identified and clustered into their propagating wavefronts. Propagation velocity was estimated by fitting a polynomial surface to the activation times. The fit was able to estimate the velocity of spike burst patches covering at least six channels with an average RMSE of 0.4 s. Propagation within patches was visualized by plotting the fit as activation maps and velocity maps. Average velocities were calculated to compare the propagation characteristics of different types of patches. In the future, this framework will be extended to generate amplitude maps and spike burst duration maps. These tools can be used to analyze spike patch propagation and their relationship to motility.

Five-fold Gastrointestinal Electrical Stimulation With Electromyography-based Activity Analysis: Towards Multilocular Theranostic Intestinal Implants

Background/Aims

Motility disorders are common and may affect the entire gastrointestinal (GI) tract but current treatment is limited. Multilocular sensing of GI electrical activity and variable electrical stimulation (ES) is a promising option. The aim of our study is to investigate the effects of adjustable ES on poststimulatory spike activities in 5 GI segments.

Methods

Six acute porcine experiments were performed with direct ES by 4 ES parameter sets (30 seconds, 25 mA, 500 microseconds or 1000 microseconds, 30 Hz or 130 Hz) applied through subserosal electrodes in the stomach, duodenum, ileum, jejunum, and colon. Multi-channel electromyography of baseline and post-stimulatory GI electrical activity were recorded for 3 minutes with hook needle and hook-wire electrodes. Spike activities were algorithmically calculated, visualized in a heat map, and tested for significance by Poisson analysis.

Results

Post-stimulatory spike activities were markedly increased in the stomach (7 of 24 test results), duodenum (8 of 24), jejunum (23 of 24), ileum (18 of 24), and colon (5 of 24). ES parameter analysis revealed that 80.0% of the GI parts (all but duodenum) required a pulse width of 1000 microseconds, and 60.0% (all but jejunum and colon) required 130 Hz frequency for maximum spike activity. Five reaction patterns were distinguished, with 30.0% earlier responses (type I), 42.5% later or mixed type responses (type II, III, and X), and 27.5% non-significant responses (type 0).

Conclusions

Multilocular ES with variable ES parameters is feasible and may significantly modulate GI electrical activity. Automated electromyography analysis revealed complex reaction patterns in the 5 examined GI segments.

Methods for High-Resolution Electrical Mapping in the Gastrointestinal Tract

Over the last two decades, high-resolution (HR) mapping has emerged as a powerful technique to study normal and abnormal bioelectrical events in the gastrointestinal (GI) tract. This technique, adapted from cardiology, involves the use of dense arrays of electrodes to track bioelectrical sequences in fine spatiotemporal detail. HR mapping has now been applied in many significant GI experimental studies informing and clarifying both normal physiology and arrhythmic behaviors in disease states. This review provides a comprehensive and critical analysis of current methodologies for HR electrical mapping in the GI tract, including extracellular measurement principles, electrode design and mapping devices, signal processing and visualization techniques, and translational research strategies. The scope of the review encompasses the broad application of GI HR methods from in vitro tissue studies to in vivo experimental studies, including in humans. Controversies and future directions for GI mapping methodologies are addressed, including emerging opportunities to better inform diagnostics and care in patients with functional gut disorders of diverse etiologies.

Progress in Mathematical Modeling of Gastrointestinal Slow Wave Abnormalities

Gastrointestinal (GI) motility is regulated in part by electrophysiological events called slow waves, which are generated by the interstitial cells of Cajal (ICC). Slow waves propagate by a process of "entrainment," which occurs over a decreasing gradient of intrinsic frequencies in the antegrade direction across much of the GI tract. Abnormal initiation and conduction of slow waves have been demonstrated in, and linked to, a number of GI motility disorders. A range of mathematical models have been developed to study abnormal slow waves and applied to propose novel methods for non-invasive detection and therapy. This review provides a general outline of GI slow wave abnormalities and their recent classification using multi-electrode (high-resolution) mapping methods, with a particular emphasis on the spatial patterns of these abnormal activities. The recently-developed mathematical models are introduced in order of their biophysical scale from cellular to whole-organ levels. The modeling techniques, main findings from the simulations, and potential future directions arising from notable studies are discussed.

Iterative Covariance-Based Removal of Time-Synchronous Artifacts: Application to Gastrointestinal Electrical Recordings

OBJECTIVE

The aim of this study was to develop, validate, and apply a fully automated method for reducing large temporally synchronous artifacts present in electrical recordings made from the gastrointestinal (GI) serosa, which are problematic for properly assessing slow wave dynamics. Such artifacts routinely arise in experimental and clinical settings from motion, switching behavior of medical instruments, or electrode array manipulation.

METHODS

A novel iterative Covariance-Based Reduction of Artifacts (COBRA) algorithm sequentially reduced artifact waveforms using an updating across-channel median as a noise template, scaled and subtracted from each channel based on their covariance.

RESULTS

Application of COBRA substantially increased the signal-to-artifact ratio (12.8 ± 2.5 dB), while minimally attenuating the energy of the underlying source signal by 7.9% on average ( -11.1 ± 3.9 dB).

CONCLUSION

COBRA was shown to be highly effective for aiding recovery and accurate marking of slow wave events (sensitivity = 0.90 ± 0.04; positive-predictive value = 0.74 ± 0.08) from large segments of in vivo porcine GI electrical mapping data that would otherwise be lost due to a broad range of contaminating artifact waveforms.

SIGNIFICANCE

Strongly reducing artifacts with COBRA ultimately allowed for rapid production of accurate isochronal activation maps detailing the dynamics of slow wave propagation in the porcine intestine. Such mapping studies can help characterize differences between normal and dysrhythmic events, which have been associated with GI abnormalities, such as intestinal ischemia and gastroparesis. The COBRA method may be generally applicable for removing temporally synchronous artifacts in other biosignal processing domains.

A system and method for online high-resolution mapping of gastric slow-wave activity

High-resolution (HR) mapping employs multielectrode arrays to achieve spatially detailed analyses of propagating bioelectrical events. A major current limitation is that spatial analyses must currently be performed "off-line" (after experiments), compromising timely recording feedback and restricting experimental interventions. These problems motivated development of a system and method for "online" HR mapping. HR gastric recordings were acquired and streamed to a novel software client. Algorithms were devised to filter data, identify slow-wave events, eliminate corrupt channels, and cluster activation events. A graphical user interface animated data and plotted electrograms and maps. Results were compared against off-line methods. The online system analyzed 256-channel serosal recordings with no unexpected system terminations with a mean delay 18 s. Activation time marking sensitivity was 0.92; positive predictive value was 0.93. Abnormal slow-wave patterns including conduction blocks, ectopic pacemaking, and colliding wave fronts were reliably identified. Compared to traditional analysis methods, online mapping had comparable results with equivalent coverage of 90% of electrodes, average RMS errors of less than 1 s, and CC of activation maps of 0.99. Accurate slow-wave mapping was achieved in near real-time, enabling monitoring of recording quality and experimental interventions targeted to dysrhythmic onset. This work also advances the translation of HR mapping toward real-time clinical application.

Automated algorithm for GI spike burst detection and demonstration of efficacy in ischemic small intestine

We present a novel, fully-automated gastrointestinal spike burst detection algorithm. Following pre-processing with SALPA (Wagenaar and Potter, J. Neurosci. Methods 120:113-120, 2002) and a Savitzky-Golay filter to remove unwanted low and high frequency components, candidate spike waveforms are detected utilizing the non-linear energy operator. Candidate waveforms are classified as spikes or artifact by a support vector machine. The new method achieves highly satisfactory performance with >90% sensitivity and positive prediction value. We also demonstrate an application of the new method to detect changes in spike rate and spatial propagation patterns upon induction of mesenteric ischemia in the small intestine. Spike rates were observed to transiently increase 10-20 fold for a duration of ≈600 s, relative to baseline conditions. In ischemic conditions, spike activity propagation patterns included retrograde-longitudinal wavefronts with occasional spontaneous conduction blocks, as well as self-terminating concentric-circumferential wavefronts. Longitudinal and circumferential velocities were 6.8-8.0 cm/s and 18.7 cm/s, respectively.

Experimental and Automated Analysis Techniques for High-resolution Electrical Mapping of Small Intestine Slow Wave Activity

BACKGROUND/AIMS

Small intestine motility is governed by an electrical slow wave activity, and abnormal slow wave events have been associated with intestinal dysmotility. High-resolution (HR) techniques are necessary to analyze slow wave propagation, but progress has been limited by few available electrode options and laborious manual analysis. This study presents novel methods for in vivo HR mapping of small intestine slow wave activity.

METHODS

Recordings were obtained from along the porcine small intestine using flexible printed circuit board arrays (256 electrodes; 4 mm spacing). Filtering options were compared, and analysis was automated through adaptations of the falling-edge variable-threshold (FEVT) algorithm and graphical visualization tools.

RESULTS

A Savitzky-Golay filter was chosen with polynomial-order 9 and window size 1.7 seconds, which maintained 94% of slow wave amplitude, 57% of gradient and achieved a noise correction ratio of 0.083. Optimized FEVT parameters achieved 87% sensitivity and 90% positive-predictive value. Automated activation mapping and animation successfully revealed slow wave propagation patterns, and frequency, velocity, and amplitude were calculated and compared at 5 locations along the intestine (16.4 ± 0.3 cpm, 13.4 ± 1.7 mm/sec, and 43 ± 6 µV, respectively, in the proximal jejunum).

CONCLUSIONS

The methods developed and validated here will greatly assist small intestine HR mapping, and will enable experimental and translational work to evaluate small intestine motility in health and disease.

A miniature bidirectional telemetry system for in vivo gastric slow wave recordings

Stomach contractions are initiated and coordinated by an underlying electrical activity (slow waves), and electrical dysrhythmias accompany motility diseases. Electrical recordings taken directly from the stomach provide the most valuable data, but face technical constraints. Serosal or mucosal electrodes have cables that traverse the abdominal wall, or a natural orifice, causing discomfort and possible infection, and restricting mobility. These problems motivated the development of a wireless system. The bidirectional telemetric system constitutes a front-end transponder, a back-end receiver and a graphical userinter face. The front-end module conditions the analogue signals, then digitizes and loads the data into a radio for transmission. Data receipt at the backend is acknowledged via a transceiver function. The system was validated in a bench-top study, then validated in vivo using serosal electrodes connected simultaneously to a commercial wired system. The front-end module was 35 × 35 × 27 mm3 and weighed 20 g. Bench-top tests demonstrated reliable communication within a distance range of 30 m, power consumption of 13.5 mW, and 124 h operation when utilizing a 560 mAh, 3 V battery. In vivo,slow wave frequencies were recorded identically with the wireless and wired reference systems (2.4 cycles min−1), automated activation time detection was modestly better for the wireless system (5% versus 14% FP rate), and signal amplitudes were modestly higher via the wireless system (462 versus 3 86μV; p<0.001). This telemetric system for slow wave acquisition is reliable,power efficient, readily portable and potentially implantable. The device will enable chronic monitoring and evaluation of slow wave patterns in animals and patients.0967-3334/

Automated gastric slow wave cycle partitioning and visualization for high-resolution activation time maps

High-resolution (HR) multi-electrode mapping has become an important technique for evaluating gastrointestinal (GI) slow wave (SW) behaviors. However, the application and uptake of HR mapping has been constrained by the complex and laborious task of analyzing the large volumes of retrieved data. Recently, a rapid and reliable method for automatically identifying activation times (ATs) of SWs was presented, offering substantial efficiency gains. To extend the automated data-processing pipeline, novel automated methods are needed for partitioning identified ATs into their propagation cycles, and for visualizing the HR spatiotemporal maps. A novel cycle partitioning algorithm (termed REGROUPS) is presented. REGROUPS employs an iterative REgion GROwing procedure and incorporates a Polynomial-surface-estimate Stabilization step, after initiation by an automated seed selection process. Automated activation map visualization was achieved via an isochronal contour mapping algorithm, augmented by a heuristic 2-step scheme. All automated methods were collectively validated in a series of experimental test cases of normal and abnormal SW propagation, including instances of patchy data quality. The automated pipeline performance was highly comparable to manual analysis, and outperformed a previously proposed partitioning approach. These methods will substantially improve the efficiency of GI HR mapping research.

Falling-edge, variable threshold (FEVT) method for the automated detection of gastric slow wave events in high-resolution serosal electrode recordings

High resolution (HR) multi-electrode mapping is increasingly being used to evaluate gastrointestinal slow wave behaviors. To create the HR activation time (AT) maps from gastric serosal electrode recordings that quantify slow wave propagation, it is first necessary to identify the AT of each individual slow wave event. Identifying these ATs has been a time consuming task, because there has previously been no reliable automated detection method. We have developed an automated AT detection method termed falling-edge, variable threshold (FEVT) detection. It computes a detection signal transform to accentuate the high 'energy' content of the falling edges in the serosal recording, and uses a running median estimator of the noise to set the time-varying detection threshold. The FEVT method was optimized, validated, and compared to other potential algorithms using in vivo HR recordings from a porcine model. FEVT properly detects ATs in a wide range of waveforms, making its performance substantially superior to the other methods, especially for low signal-to-noise ratio (SNR) recordings. The algorithm offered a substantial time savings (>100 times) over manual-marking whilst achieving a highly satisfactory sensitivity (0.92) and positive-prediction value (0.89).

Automated detection of gastric slow wave events and estimation of propagation velocity vector fields from serosal high-resolution mapping

High-resolution (HR; multi-electrode) recordings have led to detailed spatiotemporal descriptions of gastric slow wave activity. The large amount of data conveyed by the HR recordings demands an automated way of extracting the key measures such as activation times. In this study, a derivative-based method of identifying slow wave events was proposed. The raw signal was filtered using a second order Butterworth filter (low-pass; 10 Hz). The signal in each channel was differentiated and a threshold was taken as the 4.5x of the average of the negative first derivatives. An active event was defined where the first derivatives of the signal were more negative than the threshold. The accuracy of the method was validated against manually marked times, with a positive predictive value of 0.71. The detected activation times were interpolated using a second-order polynomial, the coefficients of which were evaluated using a previously developed least-square fitting method. The velocity fields were calculated, showing detailed spatiotemporal profile of slow wave propagation. The average of slow wave propagation velocity was 5.86 +/- 0.07 mms(-1).