부산대학교 도서관

Inverse methods for localization and characterization of cardiac and brain sources from ECG and EEG signals are notoriously ill-conditioned and thus sensitive to SNR in the measurements. Multiple recordings of the same underlying phenomenon are often available, but are contaminated by unmod-eled correlated noise such as heart motion from respiration or superposition of atrial activation or on-going EEG in the case of inter-ictal spikes or evoked response in EEG. We address here the open question of how best to incorporate these multiple recordings, comparing standard ensemble averaging, a multichannel non-linear spline-based average designed to be less sensitive to timing variations from motion or modulation, and a probalistic inverse incorporating a data-driven model of the noise correlation and using all recordings jointly. Results are tested on localizations of clincally recorded 120 lead ECGs during ventricular pacing.