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

Erickson, Jonathan; Putney, Joy; Hilbert, Douglas; Paskaranandavadivel, Niranchan; Cheng, Leo K.; O’Grady, Greg; Angeli, Timothy R.

doi:10.1109/tbme.2016.2521764

Cited by 5 publications

(4 citation statements)

References 43 publications

(70 reference statements)

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“…These methods were not suitable for the mucosal data in this study. However, now that this study has established foundational data for HR mucosal mapping, analytical algorithms and software could also be modified specifically for improvement of mucosal analysis in the future, for example, by introducing noise‐removal algorithms or optimizing detection parameters for the specific mucosal signal morphology, as has been achieved for lower SNR intestinal serosal slow waves . New algorithms for calculating velocity fields from non‐uniform electrode grids will also be necessary in the future.…”

Section: Discussionmentioning

confidence: 99%

“…However, now that this study has established foundational data for HR mucosal mapping, analytical algorithms and software could also be modified specifically for improvement of mucosal analysis in the future, for example, by introducing noise-removal algorithms or optimizing detection parameters for the specific mucosal signal morphology, as has been achieved for lower SNR intestinal serosal slow waves. [34][35][36] New algorithms for calculating velocity fields from non-uniform electrode grids will also be necessary in the future. For this study, velocity calculations from the modified Constellation™ device were performed assuming a uniform inter-electrode spacing of 11.4 mm, calculated as a representative global average uniform spacing between the 7-mm linear spacing along each spline of the device and the variable, larger circumferential spacing.…”

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confidence: 99%

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High‐resolution electrical mapping of porcine gastric slow‐wave propagation from the mucosal surface

Angeli

Paskaranandavadivel

et al. 2016

Neurogastroenterology Motil

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Background Gastric motility is coordinated by bioelectrical slow-waves, and gastric dysrhythmias are reported in motility disorders. High-resolution (HR) mapping has advanced the accurate assessment of gastric dysrhythmias, offering promise as a diagnostic technique. However, HR mapping has been restricted to invasive surgical serosal access. This study investigates the feasibility of HR mapping from the gastric mucosal surface. Methods Experiments were conducted in-vivo in 14 weaner pigs. Reference serosal recordings were performed with flexible-printed-circuit (FPC) arrays (128-192 electrodes). Mucosal recordings were performed by two methods: 1) FPC array aligned directly opposite the serosal array, and 2) cardiac mapping catheter modified for gastric mucosal recordings. Slow-wave propagation and morphology characteristics were quantified and compared between simultaneous serosal and mucosal recordings. Key Results Slow-wave activity was consistently recorded from the mucosal surface from both electrode arrays. Mucosally-recorded slow-wave propagation was consistent with reference serosal activation pattern, frequency (P≥0.3), and velocity (P≥0.4). However, mucosally-recorded slow-wave morphology exhibited reduced amplitude (65-72% reduced, P<0.001) and wider downstroke width (18-31% wider, P≤0.02), compared to serosal data. Dysrhythmias were successfully mapped and classified from the mucosal surface, accorded with serosal data, and were consistent with known dysrhythmic mechanisms in the porcine model. Conclusions & Inferences HR gastric electrical mapping was achieved from the mucosal surface, and demonstrated consistent propagation characteristics with serosal data. However, mucosal signal morphology was attenuated, demonstrating necessity for optimized electrode designs and analytical algorithms. This study demonstrates feasibility of endoscopic HR mapping, providing a foundation for advancement of minimally-invasive spatiotemporal gastric mapping as a clinical and scientific tool.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

High‐resolution electrical mapping of porcine gastric slow‐wave propagation from the mucosal surface

Angeli

Paskaranandavadivel

et al. 2016

Neurogastroenterology Motil

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“…While computer-automated algorithms can reduce artifacts in GI electrical recordings (e.g. [25,26]), a future study should address how to further minimize their impact, which may otherwise be problematic for general application in an ambulatory setting.…”

Section: Discussionmentioning

confidence: 99%

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

2023

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Objective: Gastrointestinal motility patterns can be mapped via electrical signals measured non-invasively on the body surface. However, long-term monitoring (≥ 24 hr) may be hindered by skin-irritation inherent with traditional Ag/AgCl pre-gelled ("wet") electrodes. Therefore, the aim of this work was to investigate the practical utility of using dry electrodes for GI body-surface electrical measurements.Approach: To directly compare dry versus wet electrodes, we simultaneously recorded electrical signals from both types arranged in a 9 electrode (3 × 3) array during an ≈ 2.5 hr colonic meal-response study. Wavelet-based analyses were used to identify the signature post-meal colonic cyclic motor patterns. Signal quality was assessed for each electrode type through quantitative comparison of the dominant frequency, amplitude, signal-to-noise ratio (SNR), and signal energy vs time in the colonic frequency band. 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.Main results: Dry electrodes recorded high-quality GI signals comparable to that of wet electrodes, with dominant frequency in the range 2.85 -3.25 cpm; peak-peak amplitudes of 120 ± 40 µV, and SNR in the range 7.5 -11 dB. The CWT colonic frequency band energy versus time correlation coefficient value was ≥ 0.71 for the majority of studies (6 out of 7) indicating very good agreement between dry and wet electrode signals overall. Whereas wet electrodes were rated by expert reviewers as having slightly better signal quality for identifying GI activity patterns, dry electrodes caused no skin irritation and were thus better-tolerated by all subjects.Significance: Dry electrodes are a viable option for long-term GI monitoring studies, offering a potentially more comfortable alternative to conventional wet electrode systems.

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“…Also, this method needs various optimizations to ensure convergence of the method. Erickson et al (2016) proposed an iterative artifact removal algorithm by scaling noise template computed by median CAR in each identified noisy section of the data. This algorithm finds the corrupted window of brain channels and scales the common reference obtained from the smoothed median estimate of all channels.…”

Section: Discussionmentioning

confidence: 99%

Adaptive Artifact Removal From Intracortical Channels for Accurate Decoding of a Force Signal in Freely Moving Rats

2019

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Intracortical data recorded with multi-electrode arrays provide rich information about kinematic and kinetic states of movement in the brain–machine interface (BMI) systems. Direct estimation of kinetic information such as the force from cortical data has the same importance as kinematic information to make a functional BMI system. Various types of the information including single unit activity (SUA), multiunit activity (MUA) and local field potential (LFP) can be used as an input information to extract motor commands for control of the external devices in BMI. Here we combine LFP and MUA information to improve decoding accuracy of the force signal from the multi-channel intracortical data of freely moving rats. We suggest a weighted common average referencing (CAR) algorithm in order to valid interpretation of the force decoding from different data types. The proposed spatial filter adaptively identifies contribution of the common noise on the channels employing Kalman filter method. We evaluated the efficacy of the proposed artifact algorithm on both simulation and real data. In the simulation study, the average R 2 between the original and reconstructed signal of all channels after applying the proposed artifact removal method was computed for input SNRs in the range of −45 to 0 dB. Weighted CAR method can effectively reconstruct the original signal with average R 2 higher than 0.5 for input SNRs higher than −s10 dB in case of adding simulated outlier and motion artifacts. We also show that the proposed artifact removal algorithm 33% improves the accuracy of force decoding in terms of R 2 value compared to standard CAR filters.

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

Cited by 5 publications

References 43 publications

High‐resolution electrical mapping of porcine gastric slow‐wave propagation from the mucosal surface

High‐resolution electrical mapping of porcine gastric slow‐wave propagation from the mucosal surface

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

Adaptive Artifact Removal From Intracortical Channels for Accurate Decoding of a Force Signal in Freely Moving Rats

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