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Automatic analysis of pre-ejection period during sleep using impedance cardiogram
Mohamad Forouzanfar1, Fiona C Baker1, Ian M Colrain1
1Human Sleep Research Program, Center for Health Sciences, SRI International, Menlo Park, California.
Psychophysiology
|March 6, 2019
Summary
New algorithms accurately identify and remove corrupted impedance cardiogram (ICG) cycles, improving pre-ejection period (PEP) measurements for reliable cardiac monitoring during sleep.
Area of Science:
- Cardiovascular Physiology
- Biomedical Engineering
- Sleep Medicine
Background:
- The pre-ejection period (PEP) is a key indicator of myocardial contractility and cardiac autonomic function.
- Accurate PEP measurement relies on precise identification of the B point on impedance cardiograms (ICG).
- Motion artifacts and noise during sleep recordings frequently compromise ICG signal quality and B-point detection.
Purpose of the Study:
- To develop and validate algorithms for detecting and excluding corrupted ICG cycles.
- To enable accurate automatic estimation of PEP using artifact-free ICG data during sleep.
- To assess the reliability of PEP measurement across different sleep stages and in-bed wakefulness.
Main Methods:
- Developed novel algorithms to identify corrupted ICG cycles based on signal activity levels.
- Excluded artifact-contaminated cycles before ensemble averaging.
- Utilized a previously validated automatic B-point detection algorithm on clean ICG data from overnight recordings of 20 participants.
Main Results:
- The artifact rejection algorithm achieved 87% accuracy in identifying expert-labeled corrupted ICG cycles, demonstrating robustness to various artifact types and levels.
- The B-point detection algorithm showed excellent concurrent validity, with intraclass correlations exceeding 0.98 across sleep stages and wakefulness, indicating high agreement with expert scoring.
- The combined algorithms successfully enabled reliable PEP estimation even with significant movement artifacts and signal variations common in overnight polysomnography.
Conclusions:
- The developed artifact detection and rejection algorithms significantly enhance the reliability of ICG-based PEP measurements.
- These algorithms are promising for automatic, accurate, and robust assessment of cardiac hemodynamic parameters during sleep studies.
- This approach facilitates advanced sleep applications requiring precise cardiac monitoring.
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