Application of vibration diagnostics to monitor the progression of Parkinson’s disease

The paper presents the results of a pilot study to determine the applicability and feasibility of using a method for processing and analyzing acceleration signals of upper limb tremors in the context of screening and objectively monitoring the progression of Parkinson's disease (PD) treatment using a smartphone-embedded accelerometer. The study involved 27 individuals diagnosed with PD at various stages of the disease as determined by the Hoehn-Yahr scale, and 15 healthy individuals as the control group. The study analyzed hand tremors by recording accelerations in three directional components: x, y, and z, applying appropriate normalization and parameterization. The analyzed quantities were maximum value (MV), root mean square (RMS), crest factor (CF), and peak-to-average ratio (PAPR). The statistical analysis using the Student's t-test showed that CF is the least differentiating parameter for disease states, while PAPR is the most differentiating. The obtained study results and conducted analyses demonstrate the significant potential of vibrational diagnostics of the upper limbs in diagnosing PD, and the possibility of facilitating the specialist doctor's work in the context of objectively monitoring treatment progress, not only in a contact manner but also remotely.