Time invariant multi electrode averaging for biomedical signals

One of the biggest challenges in averaging ECG or EEG signals is to overcome temporal misalignments and distortions, due to uncertain timing or complex non-stationary dynamics. Standard methods average individual leads over a collection of epochs on a time-sample by time-sample basis, even when mult...

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Bibliographic Details
Published in:2013 IEEE International Conference on Acoustics, Speech and Signal Processing Speech and Signal Processing, 2013-12, Vol.2013, p.1242-1246
Main Authors: Martinez Orellana, R., Erem, B., Brooks, D. H.
Format: Article
Language:English
Subjects:
Biomedical signal processing
Electrocardiography
Electrodes
Electroencephalography
Heart beat
Multidimensional signal processing
Noise reduction
Signal to noise ratio
Time series analysis
Torso
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Description
Summary:One of the biggest challenges in averaging ECG or EEG signals is to overcome temporal misalignments and distortions, due to uncertain timing or complex non-stationary dynamics. Standard methods average individual leads over a collection of epochs on a time-sample by time-sample basis, even when multi-electrode signals are available. Here we propose a method that averages multi electrode recordings simultaneously by using spatial patterns and without relying on time or frequency.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2013.6637849