Signal decomposition of transmembrane voltage-sensitive dye fluorescence using a multiresolution wavelet analysis.

Abstract

Fluorescence imaging of transmembrane voltage-sensitive dyes is used to study electrical activation in cardiac tissue. However, the fluorescence signals, typically, have low SNRs and may be contaminated with motion artifact. In this report, we introduce a new processing approach for fluoresced transmembrane potentials (fTmps) that is based upon a discrete wavelet transform. We show how fTmp signals can be decomposed and reconstructed to form three subsignals that contain signal noise (noise signal), the early depolarization phase of the action potential (rTmp signal), and motion artifact (rMA signal). A coiflet4 wavelet is used for fTmp decomposition and reconstruction of these subsignals. Results using fTmp signals that are contaminated with motion artifact indicate that the approach is a useful processing step to remove baseline drift, reduce noise, and reveal wavefronts. It streamlines the preprocessing of fTmps for the subsequent measurement of activation times and conduction velocities. It is a promising approach for studying wavefronts without aggressive mechanical tissue constraint or electromechanical uncoupling agents and is, useful for single-camera systems that do not provide for ratiometric imaging.