Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis

J. Victor Marcos; Roberto Hornero; Ian T. Nabney; Daniel Álvarez; Félix del Campo

doi:10.1109/IEMBS.2011.6090499

Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis

J. Victor Marcos^*, Roberto Hornero, Ian T. Nabney, Daniel Álvarez, Félix del Campo

^*Corresponding author for this work

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO ₂) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO ₂ signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO ₂ data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG).

Original language	English
Title of host publication	Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011
Publisher	IEEE
Pages	1745-1748
Number of pages	4
ISBN (Electronic)	978-1-4244-4122-8
ISBN (Print)	978-1-4244-4121-1
DOIs	https://doi.org/10.1109/IEMBS.2011.6090499
Publication status	Published - 2011
Event	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Boston (MA), United States Duration: 30 Aug 2011 → 3 Sept 2011

Publication series

Name	Conference proceedings IEEE Engineering in Medicine and Biology Society
Publisher	IEEE
ISSN (Print)	1557-170X

Conference

Conference	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated title	EMBC ’11
Country/Territory	United States
City	Boston (MA)
Period	30/08/11 → 3/09/11

Keywords

kernel entropy
bayesian

Access to Document

10.1109/IEMBS.2011.6090499

Cite this

Marcos, J. V., Hornero, R., Nabney, I. T., Álvarez, D., & del Campo, F. (2011). Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011 (pp. 1745-1748). (Conference proceedings IEEE Engineering in Medicine and Biology Society). IEEE. https://doi.org/10.1109/IEMBS.2011.6090499

Marcos, J. Victor ; Hornero, Roberto ; Nabney, Ian T. et al. / Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011. IEEE, 2011. pp. 1745-1748 (Conference proceedings IEEE Engineering in Medicine and Biology Society).

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title = "Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis",

abstract = "In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO 2) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO 2 signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO 2 data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG).",

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author = "Marcos, {J. Victor} and Roberto Hornero and Nabney, {Ian T.} and Daniel {\'A}lvarez and {del Campo}, F{\'e}lix",

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Marcos, JV, Hornero, R, Nabney, IT, Álvarez, D & del Campo, F 2011, Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis. in Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011. Conference proceedings IEEE Engineering in Medicine and Biology Society, IEEE, pp. 1745-1748, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston (MA), United States, 30/08/11. https://doi.org/10.1109/IEMBS.2011.6090499

Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis. / Marcos, J. Victor; Hornero, Roberto; Nabney, Ian T. et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011. IEEE, 2011. p. 1745-1748 (Conference proceedings IEEE Engineering in Medicine and Biology Society).

Research output: Chapter in Book/Published conference output › Conference publication

TY - GEN

T1 - Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis

AU - Marcos, J. Victor

AU - Hornero, Roberto

AU - Nabney, Ian T.

AU - Álvarez, Daniel

AU - del Campo, Félix

N1 - MEDLINE® is the source for the citation and abstract of this record.

PY - 2011

Y1 - 2011

N2 - In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO 2) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO 2 signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO 2 data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG).

AB - In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO 2) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO 2 signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO 2 data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG).

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T3 - Conference proceedings IEEE Engineering in Medicine and Biology Society

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BT - Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011

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Marcos JV, Hornero R, Nabney IT, Álvarez D, del Campo F. Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011. IEEE. 2011. p. 1745-1748. (Conference proceedings IEEE Engineering in Medicine and Biology Society). doi: 10.1109/IEMBS.2011.6090499

Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis

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Keywords

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