Name
Title | ||
|---|---|---|
Classification of Penetration--Aspiration Versus Healthy Swallows Using Dual-Axis Swallowing Accelerometry Signals in Dysphagic Subjects |
Abstract | ||
|---|---|---|
Swallowing accelerometry is a promising noninvasive approach for the detection of swallowing difficulties. In this paper, we propose an approach for classification of swallowing accelerometry recordings containing either healthy swallows or penetration-aspiration (entry of material into the airway) in dysphagic patients. The proposed algorithm is based on the wavelet packet decomposition of swallowing accelerometry signals in combination with linear discriminant analysis as a feature reduction method and Bayes classification. The proposed algorithm was tested using swallowing accelerometry signals collected from 40 patients during the regularly scheduled videoflouroscopy exam. The participants were instructed to swallow several 5-mL sips of thin liquid barium in a head neutral position. The results of our numerical analysis showed that the proposed algorithm can differentiate healthy swallows from aspiration swallows with an accuracy greater than 90%. These results position swallowing accelerometry as a valid approach for the detection of swallowing difficulties, particularly penetration-aspiration in patients suspected of dysphagia. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TBME.2013.2243730 | Biomedical Engineering, IEEE Transactions |
Keywords | Field | DocType |
Bayes methods,accelerometers,biomedical equipment,diagnostic radiography,feature extraction,medical disorders,medical signal processing,numerical analysis,signal classification,video signal processing,wavelet transforms,Bayes classification,airway,dual-axis swallowing accelerometry signal collection,dysphagic subjects,feature reduction method,head neutral position,healthy swallows,linear discriminant analysis,noninvasive approach,numerical analysis,penetration-aspiration classification,regularly scheduled videofluoroscopy exam,swallowing accelerometry recordings,swallowing difficulty detection,thin liquid barium,wavelet packet decomposition,Bayes classification,dual-axis swallowing accelerometry signals,linear discriminant analysis (LDA),wavelet transformation | Swallowing,Accelerometer,Computer science,Biomedical equipment,Electronic engineering,Dysphagia,Signal classification,Linear discriminant analysis | Journal |
Volume | Issue | ISSN |
60 | 7 | 0018-9294 |
Citations | PageRank | References |
7 | 0.62 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ervin Sejdic | 1 | 146 | 25.55 |
| Catriona M Steele | 2 | 74 | 6.11 |
| Tom Chau | 3 | 76 | 7.78 |