Name
Title | ||
|---|---|---|
Automated detection of obstructive sleep apnoea syndrome from oxygen saturation recordings using linear discriminant analysis |
Abstract | ||
|---|---|---|
Nocturnal polysomnography (PSG) is the gold-standard to diagnose obstructive sleep apnoea syndrome (OSAS). However, it is
complex, expensive, and time-consuming. We present an automatic OSAS detection algorithm based on classification of nocturnal
oxygen saturation (SaO2) recordings. The algorithm makes use of spectral and nonlinear analysis for feature extraction, principal component analysis
(PCA) for preprocessing and linear discriminant analysis (LDA) for classification. We conducted a study to characterize and
prospectively validate our OSAS detection algorithm. The population under study was composed of subjects suspected of suffering
from OSAS. A total of 214 SaO2 signals were available. These signals were randomly divided into a training set (85 signals) and a test set (129 signals)
to prospectively validate the proposed method. The OSAS detection algorithm achieved a diagnostic accuracy of 93.02% (97.00%
sensitivity and 79.31% specificity) on the test set. It outperformed other alternative implementations that either use spectral
and nonlinear features separately or are based on logistic regression (LR). The proposed method could be a useful tool to
assist in early OSAS diagnosis, contributing to overcome the difficulties of conventional PSG. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s11517-010-0646-6 | Med. Biol. Engineering and Computing |
Keywords | Field | DocType |
Obstructive sleep apnoea syndrome, Oxygen saturation, Linear discriminant analysis, Spectral analysis, Nonlinear analysis, Pattern classification | Population,Pattern recognition,Speech recognition,Feature extraction,Preprocessor,Artificial intelligence,Linear discriminant analysis,Logistic regression,Principal component analysis,Mathematics,Polysomnography,Test set | Journal |
Volume | Issue | ISSN |
48 | 9 | 1741-0444 |
Citations | PageRank | References |
17 | 1.53 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. Víctor Marcos | 1 | 75 | 7.13 |
| Roberto Hornero | 2 | 603 | 67.74 |
| Daniel Álvarez | 3 | 212 | 25.22 |
| Félix del Campo | 4 | 126 | 18.12 |
| Mateo Aboy | 5 | 297 | 40.03 |