Can one develop a biomarker to detect movement disorder types?
Date
2017
Authors
Kim, Kimoon
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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.
Description
A dissertation submitted to the Faculty of Engineering and the Built Environment,
University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the
degree of Master of Science in Engineering.
Johannesburg, 2017
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Citation
Kim, Kimoon (2017) Can one develop a biomarker to detect movement disorder types?, University of the Witwatersrand, <https://hdl.handle.net/10539/24187>