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1.
IEEE Trans Biomed Eng ; 65(2): 319-326, 2018 02.
Article in English | MEDLINE | ID: mdl-29364117

ABSTRACT

OBJECTIVE: High-resolution mapping of gastrointestinal (GI) slow waves is a valuable technique for research and clinical applications. Interpretation of high-resolution GI mapping data relies on animations of slow wave propagation, but current methods remain as rudimentary, pixelated electrode activation animations. This study aimed to develop improved methods of visualizing high-resolution slow wave recordings that increases ease of interpretation. METHODS: The novel method of "wavefront-orientation" interpolation was created to account for the planar movement of the slow wave wavefront, negate any need for distance calculations, remain robust in atypical wavefronts (i.e., dysrhythmias), and produce an appropriate interpolation boundary. The wavefront-orientation method determines the orthogonal wavefront direction and calculates interpolated values as the mean slow wave activation-time (AT) of the pair of linearly adjacent electrodes along that direction. Stairstep upsampling increased smoothness and clarity. RESULTS: Animation accuracy of 17 human high-resolution slow wave recordings (64-256 electrodes) was verified by visual comparison to the prior method showing a clear improvement in wave smoothness that enabled more accurate interpretation of propagation, as confirmed by an assessment of clinical applicability performed by eight GI clinicians. Quantitatively, the new method produced accurate interpolation values compared to experimental data (mean difference 0.02 ± 0.05 s) and was accurate when applied solely to dysrhythmic data (0.02 ± 0.06 s), both within the error in manual AT marking (mean 0.2 s). Mean interpolation processing time was 6.0 s per wave. CONCLUSION AND SIGNIFICANCE: These novel methods provide a validated visualization platform that will improve analysis of high-resolution GI mapping in research and clinical translation.


Subject(s)
Gastrointestinal Motility/physiology , Image Processing, Computer-Assisted/methods , Stomach/diagnostic imaging , Algorithms , Computer Simulation , Humans , Signal Processing, Computer-Assisted , Stomach/physiology
2.
IEEE Trans Biomed Eng ; 64(1): 166-172, 2017 01.
Article in English | MEDLINE | ID: mdl-27071158

ABSTRACT

GOAL: Analytic monitoring of electrophysiological data has become an essential component of efficient and accurate clinical care. In the gastrointestinal (GI) field, recent advances in high-resolution (HR) mapping are now providing critical information about spatiotemporal profiles of slow-wave activity in normal and disease (dysrhythmic) states. The current approach to analyze GI HR electrophysiology data involves the identification of individual slow-wave events in the electrode array, followed by tracking and clustering of events to create a spatiotemporal map. This method is labor and computationally intensive and is not well suited for real-time clinical use or chronic monitoring. METHODS: In this study, an automated novel technique to assess propagation patterns was developed. The method utilized time delays of the slow-wave signals which was computed through cross correlations to calculate velocity. Validation was performed with both synthetic and human and porcine experimental data. RESULTS: The slow-wave profiles computed via the time-delay method compared closely with those computed using the traditional method (speed difference: 7.2% ± 2.6%; amplitude difference: 8.6% ± 3.5%, and negligible angle difference). CONCLUSION: This novel method provides rapid and intuitive analysis and visualization of slow-wave activity. SIGNIFICANCE: This techniques will find major applications in the clinical translation of acute and chronic HR electrical mapping for motility disorders, and act as a screening tool for detailed detection and tracking of individual propagating wavefronts, without the need for comprehensive standard event-detection analysis.


Subject(s)
Action Potentials/physiology , Gastric Emptying/physiology , Muscle, Smooth/physiology , Myoelectric Complex, Migrating/physiology , Neural Conduction/physiology , Stomach/physiology , Algorithms , Animals , Electromyography/methods , Humans , Reproducibility of Results , Sensitivity and Specificity , Swine
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