Suppr超能文献

扩展自动化胃肠分析流程:去除胃浆膜记录中的无效慢波标记。

Extending the automated gastrointestinal analysis pipeline: Removal of invalid slow wave marks in gastric serosal recordings.

作者信息

Paskaranandavadivel Niranchan, Du Peng, Erickson Jonathan, O'Grady Gregory, Cheng Leo K

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:1938-41. doi: 10.1109/EMBC.2015.7318763.

Abstract

Gastric contractions are governed by a bioelectrical event known as slow waves. High-resolution electrical mapping has recently been applied to study complex gastric slow wave spatiotemporal propagations in detail. As these methods are translated to clinical and experimental applications, it is evident that efficient and automated methods are a necessity for analysis. Despite automated methods to detect slow wave events, manual review and correction remains necessary due to the presence of experimental noise in the recordings. Manual deletion of invalid slow wave events is time consuming and inefficient. We have therefore developed an algorithm to eliminate invalid markers of slow waves, via the use of frequency and morphological analysis. The techniques were validated with experimental data using serosal gastric slow wave recordings from animals and humans with a sensitivity of 90% and specificity of 85%. It is anticipated these methods will facilitate analyzing high-resolution slow wave mapping data and accelerate clinical translation of electrical mapping to clinical and diagnostic gastroentrology.

摘要

胃收缩受一种称为慢波的生物电活动支配。高分辨率电标测最近已被用于详细研究复杂的胃慢波时空传播。随着这些方法被转化为临床和实验应用,显然高效且自动化的方法对于分析是必要的。尽管有自动检测慢波事件的方法,但由于记录中存在实验噪声,人工审查和校正仍然是必要的。手动删除无效的慢波事件既耗时又低效。因此,我们开发了一种算法,通过使用频率和形态分析来消除慢波的无效标记。这些技术通过使用来自动物和人类的胃浆膜慢波记录的实验数据进行了验证,灵敏度为90%,特异性为85%。预计这些方法将有助于分析高分辨率慢波标测数据,并加速电标测在临床和诊断胃肠病学中的临床转化。

相似文献

1
Extending the automated gastrointestinal analysis pipeline: Removal of invalid slow wave marks in gastric serosal recordings.
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:1938-41. doi: 10.1109/EMBC.2015.7318763.
2
Automated classification of spatiotemporal characteristics of gastric slow wave propagation.
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:7342-5. doi: 10.1109/EMBC.2013.6611254.
3
High-resolution electrical mapping of porcine gastric slow-wave propagation from the mucosal surface.
Neurogastroenterol Motil. 2017 May;29(5). doi: 10.1111/nmo.13010. Epub 2016 Dec 29.
4
Improved signal processing techniques for the analysis of high resolution serosal slow wave activity in the stomach.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:1737-40. doi: 10.1109/IEMBS.2011.6090497.
5
Validation of noninvasive body-surface gastric mapping for detecting gastric slow-wave spatiotemporal features by simultaneous serosal mapping in porcine.
Am J Physiol Gastrointest Liver Physiol. 2022 Oct 1;323(4):G295-G305. doi: 10.1152/ajpgi.00049.2022. Epub 2022 Aug 2.
7
Detection of the Recovery Phase of in vivo gastric slow wave recordings.
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:6094-7. doi: 10.1109/EMBC.2015.7319782.
8
A novel retractable laparoscopic device for mapping gastrointestinal slow wave propagation patterns.
Surg Endosc. 2017 Jan;31(1):477-486. doi: 10.1007/s00464-016-4936-4. Epub 2016 Apr 29.
9
Automated classification and identification of slow wave propagation patterns in gastric dysrhythmia.
Ann Biomed Eng. 2014 Jan;42(1):177-92. doi: 10.1007/s10439-013-0906-3. Epub 2013 Sep 19.
10
Multi-channel wireless mapping of gastrointestinal serosal slow wave propagation.
Neurogastroenterol Motil. 2015 Apr;27(4):580-5. doi: 10.1111/nmo.12515. Epub 2015 Jan 20.

本文引用的文献

1
A system and method for online high-resolution mapping of gastric slow-wave activity.
IEEE Trans Biomed Eng. 2014 Nov;61(11):2679-87. doi: 10.1109/TBME.2014.2325829. Epub 2014 May 20.
2
Automated classification and identification of slow wave propagation patterns in gastric dysrhythmia.
Ann Biomed Eng. 2014 Jan;42(1):177-92. doi: 10.1007/s10439-013-0906-3. Epub 2013 Sep 19.
3
Mapping and modeling gastrointestinal bioelectricity: from engineering bench to bedside.
Physiology (Bethesda). 2013 Sep;28(5):310-7. doi: 10.1152/physiol.00022.2013.
4
Comparison of filtering methods for extracellular gastric slow wave recordings.
Neurogastroenterol Motil. 2013 Jan;25(1):79-83. doi: 10.1111/nmo.12012. Epub 2012 Sep 13.
6
Abnormal initiation and conduction of slow-wave activity in gastroparesis, defined by high-resolution electrical mapping.
Gastroenterology. 2012 Sep;143(3):589-598.e3. doi: 10.1053/j.gastro.2012.05.036. Epub 2012 May 27.
7
Improved signal processing techniques for the analysis of high resolution serosal slow wave activity in the stomach.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:1737-40. doi: 10.1109/IEMBS.2011.6090497.
8
An improved method for the estimation and visualization of velocity fields from gastric high-resolution electrical mapping.
IEEE Trans Biomed Eng. 2012 Mar;59(3):882-9. doi: 10.1109/TBME.2011.2181845. Epub 2011 Dec 26.
9
Automated gastric slow wave cycle partitioning and visualization for high-resolution activation time maps.
Ann Biomed Eng. 2011 Jan;39(1):469-83. doi: 10.1007/s10439-010-0170-8. Epub 2010 Oct 7.
10
Origin, propagation and regional characteristics of porcine gastric slow wave activity determined by high-resolution mapping.
Neurogastroenterol Motil. 2010 Oct;22(10):e292-300. doi: 10.1111/j.1365-2982.2010.01538.x. Epub 2010 Jul 6.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验