Central Sleep Apnea Detection by Means of Finger Photoplethysmography
Obstructive Sleep Apnea (OSA) and Central Sleep Apnea (CSA) are two types of Sleep Apnea (SA) with different etiologies and treatment options. Home sleep apnea testing based on photoplethysmography-derived peripheral arterial tonometry (PAT HSAT) has become the most widely deployed outpatient SA dia...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Journal of Translational Engineering in Health and Medicine |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10015850/ |
| _version_ | 1811176705121845248 |
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| author | Frederik Massie Steven Vits Ani Khachatryan Bart Van Pee Johan Verbraecken Jeroen Bergmann |
| author_facet | Frederik Massie Steven Vits Ani Khachatryan Bart Van Pee Johan Verbraecken Jeroen Bergmann |
| author_sort | Frederik Massie |
| collection | DOAJ |
| description | Obstructive Sleep Apnea (OSA) and Central Sleep Apnea (CSA) are two types of Sleep Apnea (SA) with different etiologies and treatment options. Home sleep apnea testing based on photoplethysmography-derived peripheral arterial tonometry (PAT HSAT) has become the most widely deployed outpatient SA diagnostic method. Being able to differentiate between CSA and OSA based solely on photoplethysmography-data would further increase PAT HSAT’s clinical utility. The present work proposes a method to detect CSA using finger photoplethysmography (PPG) data and evaluates the proposed method against simultaneous in-lab polysomnography (PSG). Methods: For 266 patients with a suspicion of SA, concurrent in-lab PSG and PPG data were acquired. The respiratory information embedded in the PPG data was extracted and used to train an ensemble of trees classifiers that predicts the central or obstructive nature of each respiratory event. The classifier performance was evaluated using patient-wise leave-one-out cross-validation where an expert analysis of the PSG served as ground truth. A second, independent analysis of the PSG was also evaluated against the ground truth to allow benchmarking of the PPG-based method. Results: The method achieved a sensitivity of 81%, a specificity of 99%, a positive predictive value of 90%, and a negative predictive value of 98% at the central apnea-hypopnea index cutoff of 10 events per hour of sleep. Conclusion and Significance: The present study aimed to evaluate a method to detect CSA in SA patients using only PPG data which could be used to flag CSA which in turn may aid in more optimal therapy decision making. |
| first_indexed | 2024-04-10T19:56:06Z |
| format | Article |
| id | doaj.art-79a9e3b7ed3a4c4984dfc320378b9d43 |
| institution | Directory Open Access Journal |
| issn | 2168-2372 |
| language | English |
| last_indexed | 2024-04-10T19:56:06Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Translational Engineering in Health and Medicine |
| spelling | doaj.art-79a9e3b7ed3a4c4984dfc320378b9d432023-01-28T00:00:19ZengIEEEIEEE Journal of Translational Engineering in Health and Medicine2168-23722023-01-011112613610.1109/JTEHM.2023.323639310015850Central Sleep Apnea Detection by Means of Finger PhotoplethysmographyFrederik Massie0https://orcid.org/0000-0002-9227-0635Steven Vits1Ani Khachatryan2Bart Van Pee3Johan Verbraecken4https://orcid.org/0000-0002-6087-678XJeroen Bergmann5https://orcid.org/0000-0001-7306-2630Department of Engineering, Natural Interaction Lab, University of Oxford, Oxford, U.K.Research Group LEMP, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, BelgiumEctosense, Leuven, BelgiumDepartment of Engineering, Natural Interaction Lab, University of Oxford, Oxford, U.K.Research Group LEMP, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, BelgiumDepartment of Engineering, Natural Interaction Lab, University of Oxford, Oxford, U.K.Obstructive Sleep Apnea (OSA) and Central Sleep Apnea (CSA) are two types of Sleep Apnea (SA) with different etiologies and treatment options. Home sleep apnea testing based on photoplethysmography-derived peripheral arterial tonometry (PAT HSAT) has become the most widely deployed outpatient SA diagnostic method. Being able to differentiate between CSA and OSA based solely on photoplethysmography-data would further increase PAT HSAT’s clinical utility. The present work proposes a method to detect CSA using finger photoplethysmography (PPG) data and evaluates the proposed method against simultaneous in-lab polysomnography (PSG). Methods: For 266 patients with a suspicion of SA, concurrent in-lab PSG and PPG data were acquired. The respiratory information embedded in the PPG data was extracted and used to train an ensemble of trees classifiers that predicts the central or obstructive nature of each respiratory event. The classifier performance was evaluated using patient-wise leave-one-out cross-validation where an expert analysis of the PSG served as ground truth. A second, independent analysis of the PSG was also evaluated against the ground truth to allow benchmarking of the PPG-based method. Results: The method achieved a sensitivity of 81%, a specificity of 99%, a positive predictive value of 90%, and a negative predictive value of 98% at the central apnea-hypopnea index cutoff of 10 events per hour of sleep. Conclusion and Significance: The present study aimed to evaluate a method to detect CSA in SA patients using only PPG data which could be used to flag CSA which in turn may aid in more optimal therapy decision making.https://ieeexplore.ieee.org/document/10015850/Sleep disordershome sleep apnea testingcentral sleep apneaphotoplethysmographyperipheral arterial tonometry |
| spellingShingle | Frederik Massie Steven Vits Ani Khachatryan Bart Van Pee Johan Verbraecken Jeroen Bergmann Central Sleep Apnea Detection by Means of Finger Photoplethysmography IEEE Journal of Translational Engineering in Health and Medicine Sleep disorders home sleep apnea testing central sleep apnea photoplethysmography peripheral arterial tonometry |
| title | Central Sleep Apnea Detection by Means of Finger Photoplethysmography |
| title_full | Central Sleep Apnea Detection by Means of Finger Photoplethysmography |
| title_fullStr | Central Sleep Apnea Detection by Means of Finger Photoplethysmography |
| title_full_unstemmed | Central Sleep Apnea Detection by Means of Finger Photoplethysmography |
| title_short | Central Sleep Apnea Detection by Means of Finger Photoplethysmography |
| title_sort | central sleep apnea detection by means of finger photoplethysmography |
| topic | Sleep disorders home sleep apnea testing central sleep apnea photoplethysmography peripheral arterial tonometry |
| url | https://ieeexplore.ieee.org/document/10015850/ |
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