Investigation of Phase Shifts Using AUC Diagrams: Application to Differential Diagnosis of Parkinson's Disease and Essential Tremor

This study was motivated by the well-known problem of the differential diagnosis of Parkinson's disease and essential tremor using the phase shift between the tremor signals in the antagonist muscles of patients. Different phase shifts are typical for different diseases; however, it remains unclear how this parameter can be used for clinical diagnosis. Neurophysiological papers have reported different estimations of the accuracy of this parameter, which varies from insufficient to 100%. To address this issue, we developed special types of area under the ROC curve (AUC) diagrams and used them to analyze the phase shift. Different phase estimations, including the Hilbert instantaneous phase and the cross-wavelet spectrum mean phase, were applied. The results of the investigation of the clinical data revealed several regularities with opposite directions in the phase shift of the electromyographic signals in patients with Parkinson's disease and essential tremor. The detected regularities provide insights into the contradictory results reported in the literature. Moreover, the developed AUC diagrams show the potential for the investigation of neurodegenerative diseases related to the hyperkinetic movements of the extremities and the creation of high-accuracy methods of clinical diagnosis.

Automated summary

This study aimed to address the problem of differential diagnosis between Parkinson's disease and essential tremor by analyzing the phase shift in tremor signals. Special types of area under the ROC curve (AUC) diagrams were developed to analyze the phase shift using different estimation methods. The investigation of clinical data revealed opposite regularities in the phase shift of electromyographic signals in patients with Parkinson's disease and essential tremor, providing insights into contradictory results reported in the literature and demonstrating the potential for studying neurodegenerative diseases and creating accurate clinical diagnosis methods related to hyperkinetic movements of the extremities.