Abstract
In this paper we employed a novel approach based on joint symbolic dynamics (JSD) to study interaction between respiratory phase and baroreflex activity. Electrocardiogram (ECG) and blood pressure recordings from six participants with history of heart failure were included in this study. First, the ECG R-peaks and systolic blood pressure indices were detected using parabolic fitting. Second, the respiratory signal was derived from Frank orthogonal ECG leads using QRS slopes and R-wave angles. Third, time series of R-R intervals and systolic blood pressure (SBP) were extracted, and respiratory phases were obtained using the Hilbert transform. Subsequently, each series was transformed into binary symbol vectors based on their successive changes and words of length '2' were formed. Baroreflex patterns were studied using word combinations representing baroreflex activity for specific changes in respiratory phases. Baroreflex activity was significantly higher for alternating low-high/high-low heart rate and SBP during inspiration as compared to continuous increase or decrease in heart rate and SBP (wiSBP=10,wiHR=01,wRP=11: 39.1±9.3% vs. wiSBP=00,wiHR=11,wRP=11: 6.4±3.9%, p
Original language | English (US) |
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Title of host publication | Computing in Cardiology |
Publisher | IEEE Computer Society |
Pages | 809-812 |
Number of pages | 4 |
Volume | 42 |
ISBN (Print) | 9781509006854 |
DOIs | |
State | Published - Feb 16 2016 |
Externally published | Yes |
Event | 42nd Computing in Cardiology Conference, CinC 2015 - Nice, France Duration: Sep 6 2015 → Sep 9 2015 |
Other
Other | 42nd Computing in Cardiology Conference, CinC 2015 |
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Country/Territory | France |
City | Nice |
Period | 9/6/15 → 9/9/15 |
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine
- Computer Science(all)