Name
Abstract | ||
|---|---|---|
Electrogastrogram (EGG) is a noninvasive measurement of gastric myoelectrical activity cutaneously, which is usually covered by strong artifacts. In this paper, the independent component analysis (ICA) with references was applied to separate the gastric signal from noises. The nonlinear uncorrelatedness between the desired component and references was introduced as a constraint. The results show that the proposed method can extract the desired component corresponding to gastric slow waves directly, avoiding the ordering indeterminacy in ICA. Furthermore, the perturbations in EGG can be suppressed effectively. In summary, it can be a useful method for EGG analysis in research and clinical practice. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/s00521-007-0100-3 | Neural Computing and Applications |
Keywords | Field | DocType |
independent component analysis ? independent component analysis with references ? electrogastrogram,nonlinear uncorrelatedness,gastric myoelectrical activity cutaneously,independent component analysis,slow wave,gastric signal,Electrogastrogram extraction,noninvasive measurement,useful method,clinical practice,proposed method,EGG analysis | Nonlinear system,Pattern recognition,Computer science,Clinical Practice,Models of neural computation,Algorithm,Artificial intelligence,Independent component analysis,Electrogastrogram,Artificial neural network | Journal |
Volume | Issue | ISSN |
16 | 6 | 1433-3058 |
Citations | PageRank | References |
5 | 0.91 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Peng | 1 | 5 | 0.91 |
| Qian Xiang | 2 | 6 | 1.92 |
| Ye Datian | 3 | 41 | 10.06 |