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使用隐马尔可夫模型推断肠道运动活动的力学状态。

Inference of mechanical states of intestinal motor activity using hidden Markov models.

作者信息

Wiklendt Lukasz, Costa Marcello, Dinning Phil G

机构信息

Discipline of Human Physiology, Flinders Medical Science and Technology, Flinders University, Adelaide, Australia.

出版信息

BMC Physiol. 2013 Dec 11;13:14. doi: 10.1186/1472-6793-13-14.

Abstract

BACKGROUND

Contractions and relaxations of the muscle layers within the digestive tract alter the external diameter and the internal pressures. These changes in diameter and pressure move digesting food and waste products. Defining these complex relationships is a fundamental step for neurogastroenterologists to be able define normal and abnormal gut motility.

RESULTS

Utilising an in vitro technique that allows for the simultaneous recording of intraluminal pressure (manometry) and gut diameter (video) in an isolated section of rabbit colon, we developed a technique to help define the mechanical states of the muscle at any point in space and time during actual peristaltic movements. This was achieved by directly relating the changes in pressure to the changes in diameter along the length of the gut studied. For each individual measure of pressure or diameter, 3 dynamic state components were identified; increasing or decreasing changes or a stable period. Two additional static state components, fully contracted and fully distended, were defined for the diameter. Then qualitative mechanical states of the muscle activity were defined as combinations of these state components. A hidden Markov model was used to correlate adjacent-in-time samples, and the Viterbi algorithm was used to infer the most likely sequence of mechanical states based on the observed data. From this a spatiotemporal map of the mechanical states was produced, showing the regions of active contractions, active relaxations, or passive states along the length of the gut throughout the entire recording period.

CONCLUSIONS

The identification of mechanical muscles states based on gut diameter and intraluminal pressure was possible by modelling muscle activation with a hidden Markov model.

摘要

背景

消化道内肌肉层的收缩和舒张会改变外径和内部压力。直径和压力的这些变化推动着正在消化的食物和废物。定义这些复杂关系是神经胃肠病学家能够界定正常和异常肠道蠕动的基本步骤。

结果

利用一种体外技术,该技术能够在兔结肠的离体节段中同时记录腔内压力(测压法)和肠道直径(视频),我们开发了一种技术,以帮助界定在实际蠕动运动期间空间和时间上任何点处肌肉的机械状态。这是通过将压力变化与所研究肠道长度上的直径变化直接关联来实现的。对于压力或直径的每一项单独测量,确定了3个动态状态成分;增加或减少变化或稳定期。为直径定义了另外两个静态状态成分,即完全收缩和完全扩张。然后将肌肉活动的定性机械状态定义为这些状态成分的组合。使用隐马尔可夫模型来关联时间上相邻的样本,并使用维特比算法根据观测数据推断最可能的机械状态序列。由此生成了机械状态的时空图,显示了在整个记录期内沿肠道长度的主动收缩、主动舒张或被动状态区域。

结论

通过用隐马尔可夫模型对肌肉激活进行建模,可以根据肠道直径和腔内压力识别机械肌肉状态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9ce/3909344/45e4ec37af10/1472-6793-13-14-1.jpg

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