Sleep apnea syndrome detection and classification of severity level from ECG and SpO2 signals

Ayalew, Mikiyas Petros; Nemomssa, Hundessa Daba; Simegn, Gizeaddis Lamesgin

doi:10.21037/ht-21-18

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…Statistical features are commonly extracted in the time domain, including mean, median, mode, maximum, minimum, variance, standard deviation, and entropy. These features were used in Álvarez et al (2012), ), Gutiérrez-Tobal et al (2015, Garde et al (2015Garde et al ( , 2016, Álvarez et al (2016), Jung et al (2017), Gutierrez-Tobal et al (2018, Deviaene et al (2019), Ayalew et al (2021). Power spectral density (PSD) is commonly used in frequency domain to extract features like mean frequency, median frequency, signal-tonoise ratio, signal-to-motion artifact ratio, and power spectrum deformation (as shown in figure 6).…”

Section: Appendix Automated System For Detection Of Sleep Apnea Using...mentioning

confidence: 99%

Pulse oximetry SpO ₂ signal for automated identification of sleep apnea: a review and future trends

Sharma

Kumar

et al. 2022

Physiol. Meas.

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Sleep apnea (SA) is characterized by intermittent episodes of apnea or hypopnea—paused or reduced breathing, respectively—each lasting at least ten seconds that occur during sleep. SA has an estimated global prevalence of 200 million and is associated with medical co-morbidities, and sufferers are also more likely to sustain traffic- and work-related injury due to daytime somnolence. SA is amenable to treatment if detected early. Polysomnography (PSG) involving multi-channel signal acquisition is the reference standard for diagnosing SA but is onerous and costly. For home-based detection of SA, single-channel SpO2 signal acquisition using portable pulse oximeters is feasible. Machine (ML) and deep learning (DL) models have been developed for the automated classification of SA versus no SA using SpO2 signals alone. In this work, we review studies published between 2012 and 2022 on the use of ML and DL for SpO2 signal-based diagnosis of SA. . A literature search based on PRISMA recommendations yielded 297 publications, of which 31 were selected after considering the inclusion and exclusion criteria. There were 20 ML and 11 DL models; their methods, differences, results, merits, and limitations were discussed. Many studies reported encouraging performance, which indicates the utility of SpO2 signals in wearable devices for home-based SA detection.

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Section: Appendix Automated System For Detection Of Sleep Apnea Using...mentioning

confidence: 99%

Pulse oximetry SpO ₂ signal for automated identification of sleep apnea: a review and future trends

Sharma

Kumar

et al. 2022

Physiol. Meas.

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Detection of Cardiac Arrhythmias in Patients with Obstructive Sleep Apnea using Machine Learning and Deep Learning Algorithms

Krithik,

Padmashree,

Nayak

et al. 2024

2024 Second International Conference on Data Science and Information System (ICDSIS)

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Patients’ Satisfaction after the Treatment of Moderate Sleep Apnea and Nocturnal Bruxism with Botox or/and Thermoformed Occlusal Splints: A Pilot Study

Rezk Gavrilă,

Bechir,

Nicolau

et al. 2024

JPM

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Background: Sleep apnea and nocturnal bruxism belong to sleep disorders that can affect the quality of life. The aim of this study was to investigate the effects on patients with moderate sleep apnea and nocturnal bruxism of Botox injection as monotherapy or associated with wearing thermoformed occlusal splints and to determine the patients’ satisfaction degree after the applied treatments. Methods: The selected patients for study were divided into two groups: in the first group, the patients (n = 18) treatment consisted of injecting Botox (Allergan) into the masseter muscle as monotherapy; in the second group, the patients (n = 18) benefited from associated therapy, Botox injections in masseter muscle, and the wear of thermoformed occlusal splints. At baseline, at three weeks, at three months, and six months after the effectuation of therapies, the monitoring sessions were realized. Results: The associated therapy presented better results in decreasing the studied symptoms than the monotherapy. Both therapies improved patient satisfaction. Conclusions: The applied therapies for treating the specific symptomatology in moderate sleep apnea and sleep bruxism were efficacious. Patient satisfaction was very good in both groups after the applied treatments, but the associated therapy presented better results than monotherapy.

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Sleep apnea syndrome detection and classification of severity level from ECG and SpO2 signals

Cited by 3 publications

References 17 publications

Pulse oximetry SpO ₂ signal for automated identification of sleep apnea: a review and future trends

Pulse oximetry SpO ₂ signal for automated identification of sleep apnea: a review and future trends

Detection of Cardiac Arrhythmias in Patients with Obstructive Sleep Apnea using Machine Learning and Deep Learning Algorithms

Patients’ Satisfaction after the Treatment of Moderate Sleep Apnea and Nocturnal Bruxism with Botox or/and Thermoformed Occlusal Splints: A Pilot Study

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Sleep apnea syndrome detection and classification of severity level from ECG and SpO2 signals

Cited by 3 publications

References 17 publications

Pulse oximetry SpO 2 signal for automated identification of sleep apnea: a review and future trends

Pulse oximetry SpO 2 signal for automated identification of sleep apnea: a review and future trends

Detection of Cardiac Arrhythmias in Patients with Obstructive Sleep Apnea using Machine Learning and Deep Learning Algorithms

Patients’ Satisfaction after the Treatment of Moderate Sleep Apnea and Nocturnal Bruxism with Botox or/and Thermoformed Occlusal Splints: A Pilot Study

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Product

Resources

About

Pulse oximetry SpO ₂ signal for automated identification of sleep apnea: a review and future trends

Pulse oximetry SpO ₂ signal for automated identification of sleep apnea: a review and future trends