Name
Title | ||
|---|---|---|
Bowel-sound pattern analysis using wavelets and neural networks with application to long-term, unsupervised, gastrointestinal motility monitoring |
Abstract | ||
|---|---|---|
This work focuses on the implementation of an autonomous system appropriate for long-term, unsupervised monitoring of bowel sounds, captured by means of abdominal surface vibrations. The autonomous intestinal motility analysis system (AIMAS) promises to deliver new potentials in gastrointestinal auscultation, towards the establishment of novel non-invasive methods for prolonged intestinal monitoring and diagnosis over functional disorders. The system was developed utilizing time-frequency features and wavelet-adapted parameters in combination with multi-layer perceptrons, that exhibit remarkable adaptation in pattern classification applications. Various network topologies and sizes were tested in combination with different features' sets. Quantitative analysis and validation results showed that the implemented system exhibits an overall recognition accuracy of 94.84%, while the error in separating bowel sounds from other sound patterns, representing interfering noises, was 2.19%. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.eswa.2006.08.014 | Expert Syst. Appl. |
Keywords | Field | DocType |
unsupervised monitoring,multi-layer perceptron,neural network,different feature,abdominal surface vibration,functional disorder,gastrointestinal auscultation,prolonged intestinal monitoring,bowel sounds,autonomous system,pattern classification,pattern recognition,wavelet,autonomous intestinal motility analysis,quantitative analysis,abdominal vibration,bowel-sound pattern analysis,exhibit remarkable adaptation,bioacoustics,gastrointestinal motility monitoring,multi layer perceptron,network topology,time frequency,pattern analysis | Computer science,Bioacoustics,Speech recognition,Network topology,Multilayer perceptron,Autonomous system (mathematics),Artificial intelligence,Auscultation,Artificial neural network,Perceptron,Machine learning,Wavelet | Journal |
Volume | Issue | ISSN |
34 | 1 | Expert Systems With Applications |
Citations | PageRank | References |
18 | 1.10 | 37 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Charalampos Dimoulas | 1 | 104 | 12.35 |
| G. Kalliris | 2 | 277 | 14.72 |
| George Papanikolaou | 3 | 80 | 7.07 |
| V. Petridis | 4 | 18 | 1.10 |
| A. Kalampakas | 5 | 50 | 2.85 |