Abstract
Spirography is a standard neurological test that has been commonly used for essential tremor diagnosis and its severity assessment for years. However, current spirography analysis is handled by Fourier Transformation (FT) on acquired data only. Frequency spectrum information through FT, such as frequency distributions, magnitudes of selected frequencies, has been the only information reported in other studies. This thesis provides a brief introduction of Essential Tremor and the application of spirography. In order to validate the algorithms developed in this study, we have created algorithmic simulations for smooth spirals and spirals with tremor oscillation. The developed simulation approach is the first of the two primary contributions of this thesis to the Essential Tremor study. Two chapters for spirography processing in frequency domain and spatial domain describe processing algorithms applied to simulated data sets and tremor patients’ spirography data sets. These two chapters discuss, test and compare two methods in frequency domain analysis to get the dominant frequency related information, along with two methods in spatial domain analysis, one aiming at unwrap the spiral-wired graph, the other designed to quantify the amplitude of tremor oscillation movement. The developed method in spatial domain is the second of the two primary contributions of this thesis to the Essential Tremor study. In the Discussion and Conclusion Chapter, we discuss current obstacles in spirography analysis and further development direction. Suggestions to handle patient spirography data are also provided in this Chapter.