scholarly journals Diagnosis of Type 2 Diabetes Using Electrogastrograms: Extraction and Genetic Algorithm–Based Selection of Informative Features

10.2196/20932 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e20932
Author(s):  
Paramasivam Alagumariappan ◽  
Kamalanand Krishnamurthy ◽  
Sundravadivelu Kandiah ◽  
Emmanuel Cyril ◽  
Rajinikanth V
Keyword(s):  
Genetic Algorithm ◽  
Fractal Dimension ◽  
Selection Process ◽  
Classification Systems ◽  
Automated Classification ◽  
Healthy Individuals ◽  
Clinical Tool ◽  
Gastric Myoelectrical Activity ◽  
Myoelectrical Activity ◽  
Box Counting

Background Electrogastrography is a noninvasive electrophysiological procedure used to measure gastric myoelectrical activity. EGG methods have been used to investigate the mechanisms of the human digestive system and as a clinical tool. Abnormalities in gastric myoelectrical activity have been observed in subjects with diabetes. Objective The objective of this study was to use the electrogastrograms (EGGs) from healthy individuals and subjects with diabetes to identify potentially informative features for the diagnosis of diabetes using EGG signals. Methods A total of 30 features were extracted from the EGGs of 30 healthy individuals and 30 subjects with diabetes. Of these, 20 potentially informative features were selected using a genetic algorithm–based feature selection process. The selected features were analyzed for further classification of EGG signals from healthy individuals and subjects with diabetes. Results This study demonstrates that there are distinct variations between the EGG signals recorded from healthy individuals and those from subjects with diabetes. Furthermore, the study reveals that the features Maragos fractal dimension and Hausdorff box-counting fractal dimension have a high degree of correlation with the mobility of EGGs from healthy individuals and subjects with diabetes. Conclusions Based on the analysis on the extracted features, the selected features are suitable for the design of automated classification systems to identify healthy individuals and subjects with diabetes.

scholarly journals Diagnosis of Type 2 Diabetes Using Electrogastrograms: Extraction and Genetic Algorithm–Based Selection of Informative Features (Preprint)

2020 ◽  
Author(s):  
Paramasivam Alagumariappan ◽  
Kamalanand Krishnamurthy ◽  
Sundravadivelu Kandiah ◽  
Emmanuel Cyril ◽  
Rajinikanth V
Keyword(s):  
Genetic Algorithm ◽  
Fractal Dimension ◽  
Selection Process ◽  
Classification Systems ◽  
Automated Classification ◽  
Healthy Individuals ◽  
Clinical Tool ◽  
Gastric Myoelectrical Activity ◽  
Myoelectrical Activity ◽  
Box Counting

BACKGROUND Electrogastrography is a noninvasive electrophysiological procedure used to measure gastric myoelectrical activity. EGG methods have been used to investigate the mechanisms of the human digestive system and as a clinical tool. Abnormalities in gastric myoelectrical activity have been observed in subjects with diabetes. OBJECTIVE The objective of this study was to use the electrogastrograms (EGGs) from healthy individuals and subjects with diabetes to identify potentially informative features for the diagnosis of diabetes using EGG signals. METHODS A total of 30 features were extracted from the EGGs of 30 healthy individuals and 30 subjects with diabetes. Of these, 20 potentially informative features were selected using a genetic algorithm–based feature selection process. The selected features were analyzed for further classification of EGG signals from healthy individuals and subjects with diabetes. RESULTS This study demonstrates that there are distinct variations between the EGG signals recorded from healthy individuals and those from subjects with diabetes. Furthermore, the study reveals that the features Maragos fractal dimension and Hausdorff box-counting fractal dimension have a high degree of correlation with the mobility of EGGs from healthy individuals and subjects with diabetes. CONCLUSIONS Based on the analysis on the extracted features, the selected features are suitable for the design of automated classification systems to identify healthy individuals and subjects with diabetes.

scholarly journals TRANSCUTANEOUS MULTICHANNEL ELECTROGASTROGRAPHY: NORMAL PARAMETERS IN A BRAZILIAN POPULATION

2020 ◽  
Vol 57 (4) ◽  
pp. 428-433
Author(s):  
Nayara Salgado CARVALHO ◽  
Diego Cardoso BAIMA ◽  
Ricardo Correa BARBUTI ◽  
Paulo Jose Pereira Campos CARVALHO ◽  
Joffre REZENDE FILHO ◽  
...  
Keyword(s):  
Dominant Frequency ◽  
Brazilian Population ◽  
Healthy Individuals ◽  
Gastric Myoelectrical Activity ◽  
Noninvasive Technique ◽  
Solid Meal ◽  
Myoelectrical Activity ◽  
Recurrent Vomiting ◽  
A Prospective Study ◽  
Instability Coefficient

ABSTRACT BACKGROUND: Electrogastrography (EGG) is a noninvasive technique for the assessment of gastric myoelectrical activity using electrodes placed on the abdominal surface. Changes in gastric myoelectrical activity may be associated with diseases such as gastroparesis, functional dyspepsia, nausea, and recurrent vomiting. In Brazil, no studies to date have assessed gastric myoelectrical activity using multichannel EGG in healthy individuals. OBJECTIVE: To establish normal values of transcutaneous multichannel EGG in healthy Brazilian individuals. METHODS: This was a prospective study including 20 healthy individuals who underwent EGG. Recording was performed during two periods: a preprandial recording was performed for 30 minutes, and a postprandial recording was performed for 30 minutes after a soft-solid meal of 400 kcal (20 grams of proteins, 60 grams of carbohydrates, and 9 grams of fat). RESULTS: We assessed dominant frequency (DF) parameters, %DF distribution, the instability coefficient, and the power ratio (PR). A total of 20 individuals (11 women and 9 men) with a mean age of 39.5±7.4 years were included. Mean DF (95%CI) ranged from 2.4 to 3.1 cpm in the resting phase and 2.6 to 3.2 cpm in the postprandial period. The %DF in normogastria range was >70% in all healthy individuals. We identified that only one individual did not present a positive response to the test meal, and the other 19 individuals showed a PR greater than 1. The instability coefficient did not change significantly with meal intake. CONCLUSION: Multichannel EGG may be applied in future studies to evaluate gastric motility disorders in the Brazilian population.

Effects of human milk and infant formula on the development of gastric myoelectrical activity in preterm infants

2001 ◽  
Vol 120 (5) ◽  
pp. A265-A265 ◽  
Author(s):  
H OUYANG ◽  
J HAYES ◽  
H ZHU ◽  
J YIN ◽  
E CO ◽  
...  
Keyword(s):  
Human Milk ◽  
Infant Formula ◽  
Preterm Infants ◽  
Gastric Myoelectrical Activity ◽  
Myoelectrical Activity

3D box-counting algorithm for calculating fractal dimension of cities

2010 ◽  
Vol 30 (8) ◽  
pp. 2070-2072
Author(s):  
Le-shan ZHANG ◽  
Ge CHEN ◽  
Yong HAN ◽  
Tao ZHANG
Keyword(s):  
Fractal Dimension ◽  
Box Counting ◽  
Counting Algorithm

Serosal and cutaneous recordings of gastric myoelectrical activity in patients with gastroparesis

1994 ◽  
Vol 266 (1) ◽  
pp. G90-G98 ◽  
Author(s):  
J. D. Chen ◽  
B. D. Schirmer ◽  
R. W. McCallum
Keyword(s):  
Electrical Stimulation ◽  
Slow Wave ◽  
Test Meal ◽  
Frequency Change ◽  
Fasting State ◽  
Gastric Myoelectrical Activity ◽  
Myoelectrical Activity ◽  
Gastric Slow Wave ◽  
Student’S T ◽  
Student’S T Test

The aims of this study were to 1) investigate gastric myoelectrical activity in patients with gastroparesis, 2) validate the cutaneous electrogastrogram (EGG) in tracking the frequency change of the gastric slow wave, and 3) investigate the effect of electrical stimulation on gastric myoelectrical activity. Gastric myoelectrical activity was recorded in 12 patients with documented gastroparesis using serosal electrodes for > 200 min in each subject. All recordings were made at least 4 days after surgery. Each session consisted of a 30-min recording in the fasting state and a 30-min recording after a test meal. The test meal (liquid or mixed) was selected according to patient's tolerance. Electrical stimulation was performed in three subjects via the serosal electrodes at a frequency of 3 cycles/min. Gastric myoelectrical activity was recorded using serosal electrodes in each session. The serosal recording showed slow waves of 2.5 to 4.0 cycles/min in all 12 subjects. Absence of spikes was noted in 11 of the 12 subjects. The simultaneous serosal and cutaneous recording of gastric myoelectrical activity showed that the frequency of the EGG was exactly the same as that of the serosal recording. Liquid meals resulted in a significant decrease in slow-wave frequency (Student's t test, P = 0.006), and the EGG accurately reflected this change. Electrical stimulation had no effect on the frequency of the gastric slow wave and did not induce spikes.(ABSTRACT TRUNCATED AT 250 WORDS)

scholarly journals Supramolecular Fractal Growth of Self-Assembled Fibrillar Networks

Gels ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 46
Author(s):  
Pedram Nasr ◽  
Hannah Leung ◽  
France-Isabelle Auzanneau ◽  
Michael A. Rogers
Keyword(s):  
Fractal Dimension ◽  
Crystallization Temperature ◽  
Cayley Tree ◽  
Fractal Dimensions ◽  
Self Similarity ◽  
Avrami Model ◽  
Cluster Aggregation ◽  
Box Counting ◽  
Self Assembled ◽  
Limited Diffusion

Complex morphologies, as is the case in self-assembled fibrillar networks (SAFiNs) of 1,3:2,4-Dibenzylidene sorbitol (DBS), are often characterized by their Fractal dimension and not Euclidean. Self-similarity presents for DBS-polyethylene glycol (PEG) SAFiNs in the Cayley Tree branching pattern, similar box-counting fractal dimensions across length scales, and fractals derived from the Avrami model. Irrespective of the crystallization temperature, fractal values corresponded to limited diffusion aggregation and not ballistic particle–cluster aggregation. Additionally, the fractal dimension of the SAFiN was affected more by changes in solvent viscosity (e.g., PEG200 compared to PEG600) than crystallization temperature. Most surprising was the evidence of Cayley branching not only for the radial fibers within the spherulitic but also on the fiber surfaces.

CT Image Analysis on the Meso-Damage of Construction Waste Recycled Brick

2012 ◽  
Vol 588-589 ◽  
pp. 1930-1933
Author(s):  
Guo Song Han ◽  
Hai Yan Yang ◽  
Xin Pei Jiang
Keyword(s):  
Fractal Dimension ◽  
Strain Curve ◽  
Ct Image ◽  
Stress Strain Curve ◽  
Crack Evolution ◽  
Construction Waste ◽  
Box Counting ◽  
Industrial Ct ◽  
Ct Image Analysis ◽  
Box Counting Method

Based on industrial CT technique, Meso-mechanical experiment was conducted on construction waste recycled brick to get the real-time CT image and stress-strain curve of brick during the loading process. Box counting method was used to calculate the fractal dimension of the inner pore transfixion and crack evolution. The results showed that lots of pore in the interfacial transition zone mainly resulted in the damage of the brick. With the increase of stress, the opening through-pore appeared and crack expanded, and the fractal dimension increased.

Feature Extraction of Demagnetization Faults in Permanent-Magnet Synchronous Motors Based on Box-Counting Fractal Dimension

2011 ◽  
Vol 58 (5) ◽  
pp. 1594-1605 ◽  
Author(s):  
M D Prieto ◽  
A G Espinosa ◽  
J-R R Ruiz ◽  
Julio César Urresty ◽  
J A Ortega
Keyword(s):  
Feature Extraction ◽  
Fractal Dimension ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors ◽  
Box Counting ◽  
Demagnetization Faults

Effect of metoclopramide on gastric myoelectrical activity in patients with gastroparesis

1998 ◽  
Vol 114 ◽  
pp. A792
Author(s):  
Z.Y. Lin ◽  
R.W. McCallum ◽  
B.D. Schirmer ◽  
J.D.Z. Chen
Keyword(s):  
Gastric Myoelectrical Activity ◽  
Myoelectrical Activity
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