DocumentCode :
2041155
Title :
RSA component extraction from heart rate signal by independent component analysis
Author :
Tiinanen, Suvi ; Tulppo, M. ; Seppänen, T.
Author_Institution :
Univ. of Oulu, Oulu, Finland
fYear :
2009
fDate :
13-16 Sept. 2009
Firstpage :
161
Lastpage :
164
Abstract :
Respiratory sinus arrhythmia (RSA) is a phenomenon where heart rate changes synchronously with respiration. It can be measured by high frequency power (HF power, 0.15-0,4 Hz) of heart rate interval (RRi) series, which is an important and widely used parameter in cardiovascular research. Due to the altering respiration rates, it is important to have methods to separate the RSA from the RRi. We applied Independent Component Analysis (ICA) to extract the RSA from the RRi series. The performance of ICA was evaluated with a simulation study where real 5 min RRi (n=20) and respiration data (n=2) of spontaneously breathing males were superimposed. According to residual analysis in time and frequency domain, the extracted RSA follows the shape of simulated RSA (3.3 - 5.4% RMS error of total variability), and ICA is able to remove RSA without changing the power content of RRi (p <0.05). Thus, ICA is a capable method to extract RSA from RRi series.
Keywords :
electrocardiography; feature extraction; independent component analysis; medical signal processing; pneumodynamics; ECG; RSA component extraction; cardiovascular research; frequency 0.15 Hz to 4 Hz; heart rate interval series; independent component analysis; residual analysis; respiration rates; respiratory sinus arrhythmia; Cardiology; Data mining; Frequency domain analysis; Frequency measurement; Hafnium; Heart rate; Heart rate interval; Independent component analysis; Power measurement; Rail to rail inputs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology, 2009
Conference_Location :
Park City, UT
ISSN :
0276-6547
Print_ISBN :
978-1-4244-7281-9
Electronic_ISBN :
0276-6547
Type :
conf
Filename :
5445444
Link To Document :
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