Characterization of Electrophysiological Propagation by Multichannel Sensors
| Autor: | Juliana H. Kim, William O. Richards, Suseela Somarajan, Leo K. Cheng, L. Alan Bradshaw |
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| Rok vydání: | 2016 |
| Předmět: |
Swine
Wave propagation Acoustics 0206 medical engineering Biomedical Engineering 02 engineering and technology Models Biological Noise (electronics) Article 03 medical and health sciences 0302 clinical medicine Position (vector) Animals Physics Stomach Signal Processing Computer-Assisted 020601 biomedical engineering Electrophysiological Phenomena Characterization (materials science) Magnetic field Electrophysiology Experimental animal 030211 gastroenterology & hepatology Gastrointestinal Motility Current density Algorithms Biomedical engineering |
| Zdroj: | IEEE Transactions on Biomedical Engineering. 63:1751-1759 |
| ISSN: | 1558-2531 0018-9294 |
| DOI: | 10.1109/tbme.2015.2502065 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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