Electrocardiogram breathing: A study of electrocardiogram derived respiration plus multiresolution wavelet analysis of heartbeat interval variability in sleep study patients
Abstract
This dissertation presents a unique research opportunity by using recordings which provide electrocardiogram (ECG) plus a reference breathing signal (RBS). ECG derived breathing (EDR) is measured and correlated against RBS. Standard deviations of multiresolution wavelet analysis coefficients (SDMW) are obtained from heart rate and classified using RBS. Prior works by others used select patients for sleep apnea scoring with EDR but no RBS. Another prior work classified select heart disease patients with SDMW but no RBS. This study used randomly chosen sleep disorder patient recordings; central and obstructive apneas, with and without heart disease. Implementation required creating an application because existing systems were limited in power and scope. A review survey was created to choose a development environment. The survey is presented as a learning tool and teaching resource. Development objectives were rapid development using limited resources (manpower and money). Open Source resources were used exclusively for implementation. Results show: (1) Three groups of patients exist in the study. Grouping RBS correlations shows a response with either ECG interval or amplitude variation. A third group exists where neither ECG intervals nor amplitude variation correlate with breathing. (2) Previous work done by other groups analyzed SDMW. Similar results were found in this study but some subjects had higher SDMW, attributed to a large number of apneas, arousals and/or disconnects. SDMW does not need RBS to show apneic conditions exist within ECG recordings. (3) Results in this study support the assertion that autonomic nervous system variation was measured with SDMW. Measurements using RBS are not corrupted due to breathing even though respiration overlaps the same frequency band. Overall, this work becomes an Open Source resource which can be reused, modified and/or expanded. It might fast track additional research. In the future the system could also be used for public domain data. Prerecorded data exist in similar formats in public databases which could provide additional research opportunities.
Subject Area
Biomedical research|Electrical engineering
Recommended Citation
Watson, Herman Lanier, "Electrocardiogram breathing: A study of electrocardiogram derived respiration plus multiresolution wavelet analysis of heartbeat interval variability in sleep study patients" (2007). ProQuest ETD Collection for FIU. AAI3268674.
https://digitalcommons.fiu.edu/dissertations/AAI3268674