胃食管反流病胃电活动变化的研究

目的　探讨胃食管反流病 (GERD)的胃电活动变化。方法　主诉反流症状的患者 ,经 2 4小时食管酸、碱监测和 (或 )胃镜检查 ,GERD 43例 ,健康对照组 3 9例 ,进行餐前、餐后体表胃电图 (EGG)监测。结果　GERD组的平均正常胃电慢波百分比 ( 63 .40 %± 3 1.63 %)显著低于对照组 ( 80 .89%± 2 5 .42 %) ,餐前胃电节律异常的发生率 ( 5 8.1%)显著高于对照组 ( 17.0 %) ,餐前主频不稳定系数 ( 5 3 .6± 5 0 .8)也显著高于对照组 ( 3 4.2± 3 3 .1) ;GERD组的餐后胃电节律异常的发生率 ( 3 2 .6%)显著高于对照组 ( 12 .8%)。结论　GERD患者存在餐前、餐后胃电活动异常 ,体表EGG检查有助于了解GERD的胃运动功能情况     

功能性消化不良消化间期和消化期体表胃电变化规律

目的:观察正常人及消化不良病人消化间期和消化期EGG的动态变化规律及探讨餐后胃电与胃窦机械收缩之间的偶联关系。方法:采用PC Polygraph HR台式高分辨上消化道动力监测系统对11例正常人和14例功能性消化不良(FD)病人连续5小时同步记录体表胃电和胃窦幽门十二指肠压力变化。结果:正常人胃电功率随消化间期移行性复合运动(MMC)的周期变化而变化,Ⅱ期时增高,约为Ⅰ期的2倍,Ⅲ期最高,约为Ⅰ期的2.5倍,餐后功率与Ⅲ期接近,FD病人胃电功率只在餐后30分升高。消化间期胃电功率和胃窦动力指数呈正相关(正常组:r=0.87,P<0.01;FD组:r=0.79,P<0.01)。结论:体表胃电可以反映MMC周期性变化和胃窦运动功能。FD病人餐后胃电功率减低。     

甲状腺机能亢进和减退患者的胃电图改变初探

目的通过胃电图(EGG)检查,观察32例甲状腺机能亢进(甲亢)病人,29名甲状腺机能减退(甲减)病人及30名正常健康人餐前和餐后30min的体表胃电频谱变化。结果3组内餐后胃电图主频(DF)、平均幅值(AP)、正常慢波百分比(N%)与餐前相比均有显著增加(P<0.01)。甲亢组主频和平均幅值与对照组相比,无显著差异(P>0.05),甲减组平均幅值与正常慢波百分比较对照组差异显著(P<0.01)。结论甲亢组食欲亢进在胃电图上无特殊反映,表现为主频正常,胃电节律正常,振幅亦无明显升高。甲减组食欲减退可能与胃动过缓,胃电节律紊乱增多有关。     

窒息后新生儿胃电活动的研究

目的　利用胃电图探讨窒息对新生儿胃电活动的影响。　方法　采用瑞典 CTd-synec-tics公司生产的便携式胃电图 ( EGG)记录仪对 50例窒息后新生儿和 2 0例正常新生儿进行了喂奶前、后各 3 0 min的胃电活动的检测 ,利用计算机 EGG Version6.4 0软件分析系统分析数据。　结果　 70例新生儿有 3 9例 ( 56% )成功记录到 EGG。轻度窒息组与对照组比较 ,喂奶前胃动过缓 ( <2cpm)百分比增多 ( 7.0± 6.8与 4 .7± 5.4 ) ,差异有非常显著意义 ( P<0 .0 1 )。重度窒息组与对照组及轻度窒息组比较 :喂奶前、后正常慢波百分比明显降低 ( P<0 .0 1 ) ,胃动过速 ( >4 cpm)百分比明显增多 ( P<0 .0 1 )。主功频率不稳定系数 ( DFIC)增高 ( P<0 .0 1 )。　结论　EGG可以用来研究窒息后新生儿的胃电活动 ,进而研究新生儿消化道动力 ;围产期轻度窒息新生儿喂奶前胃动过缓增多 ,重度窒息新生儿喂奶前、后正常慢波百分比明显降低 ,胃动过速百分比明显增多 ,提示围产期窒息的新生儿出现拒乳、腹胀、呕吐等症状 ,可能与其胃电节律异常有关。     

胃食管反流病患者体表胃电节律的变化规律

目的观察胃食管反流病（GERD）患者的体表胃电节律变化规律及其与患者症状间的关系。方法采用PCPolyg。印hHR双电极胃电记录仪记录25例GERD患者（GERD组）和12例健康人（对照组）的餐前和餐后胃电正常节律的百分比、胃动过缓的百分比、胃动过速的百分比、主频率（DF）、餐后与餐前主功率之比（PR）、DF不稳定系数（DFIC），以及不同症状积分的GERD患者正常节律的百分比、DF、DFIC。结果GERD组患者餐前、餐后胃电正常节律的百分比、DF低于对照组，胃动过缓的百分比、胃动过速的百分比、DFIC均高于对照组，差异有统计学意义。GERD组患者餐前胃电正常节律的百分比、DF低于餐后，而胃动过缓的百分比、DFIC高于餐后，差异有统计学意义。不同症状积分的GERD组患者餐前、餐后胃电节律参数与对照组相比差异均有统计学意义，但各积分组间胃电节律参数差异无统计学意义。结论GERD患者存在胃电生理活动的异常，这种异常可能是GERD的发病机制之一。     

Detection of gastric dysrhythmia using WT and ANN in diabetic gastroparesis patients

Gastric myoelectrical activity can be measured by a noninvasive technique called electrogastrography where surface electrodes are placed on the epigastric area of the abdomen. The electrogastrogram (EGG) signal is by nature a nonstationary signal in terms of its frequency, amplitude and wave shape. Unlike the other methods discrete wavelet analysis (DWT) was designed for nonstationary signals. For automatic assessment of EGG, we used artificial neural networks (ANNs) that have been widely employed in pattern recognition due to their great potential of high performance, flexibility, robust fault tolerance, cost-effective functionality and capability for real-time applications. So we developed a new method for classification of EGG based on DWT and ANN.     

Adaptive filtering of canine electrogastrographic signals. Part 2: filter performance

The modified adaptive filter method described in Part 1 was applied to 16 stretches of (cutaneous) electrogastrographic signal of 17·07 min duration. A signal-to-noise ratio improvement of about 8 dB was achieved. The most characteristic feature of the filter method appeared to be that wave-form and phase of the gastric component of the electrogastrographic signal are preserved. It is concluded that the use of the modified adaptive filter forms a valuable tool in the study of the electrogastrographic signal.     

Detection and deletion of motion artifacts in electrogastrogram using feature analysis and neural networks

Electrogastrogram is a surface measurement of gastric myoelectrical activity, and electrogastrography has been an attractive method for physiological and pathophysiological studies of the stomach due to its nonivasive nature. Motion artifacts, however, ruin the electrogastrogram (EGG), and make the analysis very difficult and sometimes even impossible. They must be eliminated from EGG signals before analysis. Up to now, this can only be done by visual inspection, which is not only time-consuming but also subjective. In this study, a method using feature analysis and neural networks has been developed to realize automatic detection and elimination of the motion artifacts in EGG recordings by computer. Experiments were conducted to investigate the characteristics of different motion artifacts. Useful features were extracted, and different combinations of the features used as the input of the neural network were compared to obtain the optimal performance for the detection of motion artifacts using the artificial neural network.     

Conoidal dipole model of electrical field produced by the human stomach

Spontaneous depolarisation and repolarisation due to ionic exchange are the main properties of smooth muscle cells in the human stomach. This change in the distribution of electrical charge results in the creation of an electric field. The field manifests itself as a potential difference (biovoltage), recorded both in vitro and in vivo and known as gastric electrical activity (GEA). The aim of the paper is to describe a computer model of this electric phenomenon, considering all anatomical and electrophysiological particularities of the stomach, and to simulate real in vivo experiments with a computer. In the proposed model, the depolarised smooth muscle cells are represented as organised electrical dipoles distributed with known density in an annular band that moves distally with increasing velocity. Computer simulations of in vivo experiments using this model not only give the waveform, duration, amplitude and frequency of GEA, but they also represent the phase lag between different channels, the difference in propagation velocity along greater and lesser curvatures, and the electric coupling between different parts of the stomach. The effects of changed electrode configuration, surface area and distance from the stomach are described. Mathematical modelling is done in spherical co-ordinates, and the simulations are performed in a specially designed user-friendly IBM PC environment. Some of the unsolved problems in cutaneous electrogastrography are also discussed.