Name
Title | ||
|---|---|---|
Bispectral Analysis to Enhance Oximetry as a Simplified Alternative for Pediatric Sleep Apnea Diagnosis |
Abstract | ||
|---|---|---|
This study aims at assessing the bispectral analysis of blood oxygen saturation (SpO
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) from nocturnal oximetry to help in pediatric sleep apnea-hypopnea syndrome (SAHS) diagnosis. Recent studies have found excessive redundancy in the SAHS-related information usually extracted from SpO
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, while proposing only two features as a reduced set to be used. On the other hand, it has been suggested that SpO
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bispectral analysis is able to provide complementary information to common anthropometric, spectral, and clinical variables. We address these novel findings to assess whether bispectrum provides new non-redundant information to help in SAHS diagnosis. Thus, we use 981 pediatric SpO
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recordings to extract both the reduced set of features recently proposed as well as 9 bispectral features. Then, a feature selection method based on the fast correlation-based filter and bootstrapping is used to assess redundancy among all the features. Finally, the non-redundant ones are used to train a Bayesian multi-layer perceptron neural network (BYMLP) that estimate the apnea-hypopnea index (AHI), which is the diagnostic reference variable. Bispectral phase entropy was found complementary to the two previously recommended features and a BY-MLP model trained with the three of them reached high agreement with actual AHI (intra-class correlation coefficient = 0.889). Estimated AHI also showed high diagnostic ability, reaching 82.1%, 81.9%, and 90.3% accuracies and 0.814, 0.880, and 0.922 area under the receiver-operating characteristics curve for three common AHI thresholds: 1 e/h, 5 e/h, and 10 e/h, respectively. These results suggest that the information extracted from the bispectrum of SpO
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can improve the diagnostic performance of the oximetry test. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/EMBC.2018.8512248 | 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
Keywords | Field | DocType |
Anthropometry,Bayes Theorem,Child,Female,Humans,Male,Middle Aged,Neural Networks, Computer,Oximetry,Pulmonary Gas Exchange,ROC Curve,Sleep Apnea Syndromes,Sleep Apnea, Obstructive | Correlation coefficient,Computer vision,Sleep apnea,Pattern recognition,Feature selection,Computer science,Bispectrum,Bootstrapping,Redundancy (engineering),Artificial intelligence,Perceptron,Bispectral analysis | Conference |
Volume | ISSN | ISBN |
2018 | 1557-170X | 978-1-5386-3647-3 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gonzalo C. Gutiérrez-Tobal | 1 | 31 | 10.29 |
| Leila Kheirandish-Gozal | 2 | 4 | 4.09 |
| Fernando Vaquerizo-Villar | 3 | 6 | 6.92 |
| Daniel Álvarez | 4 | 212 | 25.22 |
| Verónica Barroso-García | 5 | 6 | 6.59 |
| Andrea Crespo | 6 | 5 | 3.47 |
| Félix del Campo | 7 | 126 | 18.12 |
| David Gozal | 8 | 4 | 4.42 |
| Roberto Hornero | 9 | 603 | 67.74 |