Can one develop a biomarker to detect movement disorder types?

Abstract

This study presents the development of a potentially new biomarker for three different movement disorders: Huntington’s Disease (HD), Parkinson’s Disease (PD) and Essential Tremors (ET). A Leap Motion® gaming device was used to record the trajectories of subjects’ forefinger as they trace simple patterns in the air. The patterns used were stepfunction, triangle and circle. The recorded signals were analysed using transform functions and Fourier analysis. Both analysis types yielded features from which differences between the four categories studied: PD, HD, ET and control subjects, were sought and displayed in both graphical and numerical forms. The X-axis and Y-axis of the signals were separately analysed and yielded different results. For the step-function pattern, no distinct differences between the four categories were found from the transfer function analysis whereas the Y-axis of the signal could distinguish between the categories. For the triangle pattern, the X-axis features provided a discrimination between the categories while the Y-axis feature did not. For the circle pattern, neither X-axis nor Y-axis features were able to distinguish between the categories. A Fourier analysis showed a better discrimination ability for both X- and Y- axis. This study is a preliminary one and all results indicate that more subjects of all categories are needed to develop a bio-marker for the diseases studied and that a higher order transfer function analysis is required. However, the methodology outlined in this work, comprising of both the experimental system and the analysis showed a potential to produce a biomarker for movement disorders.