April 13, 2015IEEE Transactions on Biomedical EngineeringOpen Access

A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG

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Why the study?

Can a novel algorithm using single-lead ECG accurately detect sleep apnea?

Population

80 ECG recordings

Design

Other

Authors

CVCarolina VaronElectrophysiology ACAlexander CaicedoPontificia Universidad Javeriana DTDries TestelmansUniversitair Ziekenhuis Leuven

Discussion

Member takes

Implication

May simplify sleep apnea screening if validated; leaves open its clinical role versus polysomnography.

Structured PICO

Can a novel algorithm using single-lead ECG accurately detect sleep apnea?

Population

80 ECG recordings

Intervention

Automatic detection algorithm using a least-squares support vector machines classifier with an RBF kernel, based on novel ECG-derived features (QRS principal components, respiration/HR orthogonal subspace projections) and HRV features

Outcome

Accuracy of sleep apnea detection on a minute-by-minute basis and separation between apnea and normal recordings

A novel single-lead ECG algorithm can accurately detect sleep apnea and identify ECG artifacts, potentially offering a simpler alternative for sleep apnea screening.

Cite This Study

Varon et al. (2015) studied this question.

synapsesocial.com/papers/6a70263653da1ffdb5079d0e https://doi.org/10.1109/tbme.2015.2422378

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A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG

Discussion

Member takes

Implication

Structured PICO

Cite This Study

A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG

Discussion

Member takes

Implication

Structured PICO

Cite This Study

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Also Consider