Abstract
Fluorescence imaging of transmembrane voltage-sensitive dyes is used to study electrical activation in cardiac tissue. However, fluorescence signals typically have a low signal to noise ratio that can be contaminated with motion artifacts. We describe an alternative processing approach for fluoresced transmembrane potentials (fTmps) using the wavelet multiresolution analysis. We show that fTmp signals can be decomposed and reconstructed to form three sub-signals that contain signal noise (noise signal), the early depolarization phase of the action potential (rTmp signal), and motion artifact (rMA signal). Discrete wavelet transform is used with coiflet 4 scaling and wavelet functions for fTmp decomposition and reconstruction of these sub-signals. Our results show that this type of analysis can be used to remove baseline drift, reduce noise, and reveal wavefronts. It streamlines the preprocessing of fTmps for subsequent measurement of activation times and conduction velocities. The approach is promising for studying wave fronts without aggressive mechanical tissue constraint or electromechanical uncoupling agents, and it is particularly useful for single camera systems that do not provide for ratiometric imaging.