Noninvasive detection of small bowel electrical activity from SQUID magnetometer measurements using SOBI

Erickson, John O.; Obioha, Chibuike; Goodale, Adam; Bradshaw, Alan; Richards, William O.

doi:10.1109/iembs.2008.4649550

Cited by 5 publications

(6 citation statements)

References 13 publications

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“…In our notation, MGG or EGG refers to magnetogastrogram or electrogastrogram signals with the Butterworth digital filter applied while SOBI-MGG and SOBI-EGG refers to the same signals processed using the SOBI algorithm to identify gastric signal components. SOBI components were classified as gastric if they were primarily sinusoidal with a dominant frequency in the gastric range (2.5–4 cpm; Erickson et al , 2008; Erickson et al , 2009). …”

Section: Resultsmentioning

confidence: 99%

“…Apart from the filtering, we also applied the Second-Order Blind Identification (SOBI) signal processing algorithm to reduce the interfering noise signals. A detailed description of SOBI and its mathematical formulations are available elsewhere (Belouchrani et al , 1997; Erickson et al , 2008; Erickson et al , 2009). Furthermore, we investigated the correlation of filtered postprandial EMG signals with corresponding MGG and EGG components isolated with SOBI.…”

Section: Methodsmentioning

confidence: 99%

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Biomagnetic and bioelectric detection of gastric slow wave activity in normal human subjects—a correlation study

Somarajan¹,

Muszynski²,

Obioha³

et al. 2012

Physiol. Meas.

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We measured gastric slow wave activity simultaneously with a Superconducting Quantum Interference Device (SQUID) magnetometer, mucosal electrodes, and cutaneous electrodes in 18 normal human subjects (11 women and 7 men). We processed signals with Fourier spectral analysis and SOBI blind-source separation techniques. We observed a high waveform correlation between mucosal electromyogram (EMG) and multichannel SQUID magnetogastrogram (MGG). There was a lower waveform correlation between mucosal EMG and cutaneous electrogastrogram (EGG), but the correlation improved with application of SOBI. There was also a high correlation between the frequency of the electrical activity recorded in MGG and in mucosal electrodes (r =0.97). We concluded that SQUID magnetometers noninvasively record gastric slow wave activity that is highly correlated with the activity recorded by invasive mucosal electrodes.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Biomagnetic and bioelectric detection of gastric slow wave activity in normal human subjects—a correlation study

Somarajan¹,

Muszynski²,

Obioha³

et al. 2012

Physiol. Meas.

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“…We computed frequency spectra using the Fast Fourier Transform (FFT). For MENG signals, in addition to filtering, we also applied a Second-Order Blind Identification (SOBI) signal processing algorithm to reduce the interfering noise signals [8,17,18]. SOBI decomposes the multichannel SQUID data into separate signal and noise components.…”

Section: Discussionmentioning

confidence: 99%

Magnetoenterography for the Detection of Partial Mesenteric Ischemia

Somarajan

Muszynski

Olson

et al. 2019

Journal of Surgical Research

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BACKGROUND-Acute mesenteric ischemia represents a life-threatening gastrointestinal condition. A noninvasive diagnostic modality that identifies mesenteric ischemia patients early in the disease process will enable early surgical intervention. Previous studies have identified significant changes in the small bowel electrical slow wave (SW) parameters during intestinal ischemia caused by total occlusion of the superior mesenteric artery (SMA). The purpose of this study was to employ noninvasive biomagnetic techniques to assess functional physiological changes in intestinal slow waves in response to partial mesenteric ischemia. METHODS-We induced progressive intestinal ischemia in normal porcine subjects (N=10) by slowly increasing the occlusion of the superior mesenteric artery at the following percentages of baseline flow: 50%, 75%, 90% and 100% while simultaneous transabdominal magnetoenterogram (MENG) and serosal electromyogram (EMG) recordings were being obtained. RESULTS-A statistically significant serosal EMG amplitude decrease was observed at 100% occlusion compared to baseline while no significant change was observed for MENG amplitude at any progressive occlusion levels. MENG recordings showed significant changes in the frequency and percentage of power distributed (PPD) in brady-and normoenteric frequency ranges at 50%, 75%, 90% and 100% vessel occlusions. In serosal EMG recordings, a similar PPD effect was

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“…We downsampled and filtered signals to 30 Hz for easier processing in MATLAB (bandwidth 1-120 cpm) and computed Fast Fourier Transform (FFT) spectra (using 120-s windows with Hamming windowing) to identify the dominant frequencies of signals. The SOBI algorithm was used to decompose SQUID signals into components and noise components were eliminated [35, 39]. SOBI-reconstructed magnetic field spatiotemporal maps were composed for computation of propagation velocity.…”

Section: Methodsmentioning

confidence: 99%

Characterization of Electrophysiological Propagation by Multichannel Sensors

Bradshaw

Kim

Somarajan

et al. 2016

IEEE Trans. Biomed. Eng.

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Objective The propagation of electrophysiological activity measured by multichannel devices could have significant clinical implications. Gastric slow waves normally propagate along longitudinal paths that are evident in recordings of serosal potentials and transcutaneous magnetic fields. We employed a realistic model of gastric slow wave activity to simulate the transabdominal magnetogastrogram (MGG) recorded in a multichannel biomagnetometer and to determine characteristics of electrophysiological propagation from MGG measurements. Methods Using MGG simulations of slow wave sources in a realistic abdomen (both superficial and deep sources) and in a horizontally-layered volume conductor, we compared two analytic methods (Second Order Blind Identification, SOBI and Surface Current Density, SCD) that allow quantitative characterization of slow wave propagation. We also evaluated the performance of the methods with simulated experimental noise. The methods were also validated in an experimental animal model. Results Mean square errors in position estimates were within 2 cm of the correct position, and average propagation velocities within 2 mm/s of the actual velocities. SOBI propagation analysis outperformed the SCD method for dipoles in the superficial and horizontal layer models with and without additive noise. The SCD method gave better estimates for deep sources, but did not handle additive noise as well as SOBI. Conclusion SOBI-MGG and SCD-MGG were used to quantify slow wave propagation in a realistic abdomen model of gastric electrical activity. Significance These methods could be generalized to any propagating electrophysiological activity detected by multichannel sensor arrays.

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Noninvasive detection of small bowel electrical activity from SQUID magnetometer measurements using SOBI

Cited by 5 publications

References 13 publications

Biomagnetic and bioelectric detection of gastric slow wave activity in normal human subjects—a correlation study

Biomagnetic and bioelectric detection of gastric slow wave activity in normal human subjects—a correlation study

Magnetoenterography for the Detection of Partial Mesenteric Ischemia

Characterization of Electrophysiological Propagation by Multichannel Sensors

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