Title :
Propagation pattern analysis during atrial fibrillation based on the adaptive group LASSO
Author :
Richter, Ulrike ; Faes, Luca ; Ravelli, Flavia ; Sörnmo, Leif
Author_Institution :
Dept. of Electr. & Inf. Technol., Lund Univ., Lund, Sweden
fDate :
Aug. 30 2011-Sept. 3 2011
Abstract :
The present study introduces sparse modeling for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence (PDC) function, derived from fitting a multivariate autoregressive model to the observed signals. A sparse optimization method is proposed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO). In simulations aLASSO was found superior to the commonly used least-squares (LS) estimation with respect to estimation performance. The normalized error between the true and estimated model parameters dropped from 0.20±0.04 for LS estimation to 0.03±0.01 for aLASSO when the number of available data samples exceeded the number of model parameters by a factor of 5. The error reduction was more pronounced for short data segments. Propagation patterns were also studied on intrac-ardiac AF data, the results showing that the identification of propagation patterns is substantially simplified by the sparsity assumption.
Keywords :
autoregressive processes; diseases; least squares approximations; medical signal processing; sparse matrices; aLASSO; adaptive group; adaptive group least absolute selection and shrinkage operator; error reduction; intracardiac atrial fibrillation; least-squares estimation; multivariate autoregressive model; propagation pattern analysis; sparse modeling; sparse optimization method; Accuracy; Adaptation models; Catheters; Couplings; Estimation; Pattern analysis; Time series analysis; Algorithms; Animals; Atrial Fibrillation; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Heart Conduction System; Humans; Models, Cardiovascular; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2011.6091412