| A unique wavelet method is developed for processing transitory signals and is compared to the FFT in order to evaluate the effect of shortening pre-processed data length on spectral resolution. Both methods carry no time information, so minimization of raw data is necessary to accurately measure characteristics of short-lived biological events. After testing simulated signals in order to demonstrate each method's wavelength resolution capabilities as a function of signal length, interferometric data collected from a spectroscopic system is analyzed. It is hoped that the compactness of the wavelet transform will allow spectral data to be characterized over a shorter time span, reducing discomfort suffered by patients. It may also be an effective tool when used in conjunction with the FFT to track the course of signals that change over time, such as the motion artifacts present when collecting data from a patient. |
