ArticleAnnals of biomedical engineering2010
Falling-edge, variable threshold (FEVT) method for the automated detection of gastric slow wave events in high-resolution serosal electrode recordings.
Article in Annals of biomedical engineering, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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50 citing papers in PubMed.
- Patterns of Abnormal Gastric Pacemaking After Sleeve Gastrectomy Defined by Laparoscopic High-Resolution Electrical Mapping.Obesity surgery · 2017Trial
- Simultaneous optical imaging of gastric slow waves and contractions in the in vivo porcine stomach.American journal of physiology. Gastrointestinal and liver physiology · 2024Article
- Optimization of pacing parameters to entrain slow wave activity in the pig jejunum.Scientific reports · 2024Article
- Electromechanical Response of Mesenteric Ischemia Defined Through Simultaneous High-Resolution Bioelectrical and Video Mapping.Annals of biomedical engineering · 2024Article
- High-resolution in vivo monophasic gastric slow waves to quantify activation and recovery profiles.Neurogastroenterology and motility · 2022Article
- An automated artifact detection and rejection system for body surface gastric mapping.Neurogastroenterology and motility · 2022Article
- The influence of interstitial cells of Cajal loss and aging on slow wave conduction velocity in the human stomach.Physiological reports · 2021Article
- Article
- High-resolution Mapping of Hyperglycemia-induced Gastric Slow Wave Dysrhythmias.Journal of neurogastroenterology and motility · 2019Article
- Improved Visualization of Gastrointestinal Slow Wave Propagation Using a Novel Wavefront-Orientation Interpolation Technique.IEEE transactions on bio-medical engineering · 2018Article
- High-resolution electrical mapping of porcine gastric slow-wave propagation from the mucosal surface.Neurogastroenterology and motility · 2017Article
- Time-Delay Mapping of High-Resolution Gastric Slow-Wave Activity.IEEE transactions on bio-medical engineering · 2017Article
- A novel retractable laparoscopic device for mapping gastrointestinal slow wave propagation patterns.Surgical endoscopy · 2017Article
- Problems with extracellular recording of electrical activity in gastrointestinal muscle.Nature reviews. Gastroenterology & hepatology · 2016Review
- Acute Slow Wave Responses to High-Frequency Gastric Electrical Stimulation in Patients With Gastroparesis Defined by High-Resolution Mapping.Neuromodulation : journal of the International Neuromodulation Society · 2016Article
- Iterative Covariance-Based Removal of Time-Synchronous Artifacts: Application to Gastrointestinal Electrical Recordings.IEEE transactions on bio-medical engineering · 2016Article
- Functional physiology of the human terminal antrum defined by high-resolution electrical mapping and computational modeling.American journal of physiology. Gastrointestinal and liver physiology · 2016Article
- Simultaneous anterior and posterior serosal mapping of gastric slow-wave dysrhythmias induced by vasopressin.Experimental physiology · 2016Article
- Characterization of Electrophysiological Propagation by Multichannel Sensors.IEEE transactions on bio-medical engineering · 2016Article
- The impact of surgical excisions on human gastric slow wave conduction, defined by high-resolution electrical mapping and in silico modeling.Neurogastroenterology and motility · 2015Article
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9 authors.
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Abstract
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).
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