Finger tapping movements of Parkinson's disease patients automatically rated using nonlinear delay differential equations

Parkinson’s disease is a degenerative condition whose severity is assessed by clinical observations of motor behaviors. These are performed by a neurological specialist through subjective ratings of a variety of movements including 10-s bouts of repetitive finger-tapping movements. We present here an algorithmic rating of these movements which may be beneficial for uniformly assessing the progression of the disease. Finger-tapping movements were digitally recorded from Parkinson’s patients and controls, obtaining one time series for every 10 s bout. A nonlinear delay differential equation, whose structure was selected using a genetic algorithm, was fitted to each time series and its coefficients were used as a six-dimensional numerical descriptor. The algorithm was applied to time-series from two different groups of Parkinson’s patients and controls. The algorithmic scores compared favorably with the unified Parkinson’s disease rating scale scores, at least when the latter adequately matched with ratings from the Hoehn and Yahr scale. Moreover, when the two sets of mean scores for all patients are compared, there is a strong (r ¼ 0.785) and significant (p < 0:0015) correlation between them. V C 2012 American Institute of Physics. [doi:10.1063/1.3683444] Parkinson’s disease (PD) is a common disease affecting tens of millions of people worldwide. Its cardinal signs are resting tremor, bradykinesia (slowness clumsiness of movement), rigidity, and loss of postural reflexes. The disease evolves slowly and, to adjust medications to the severity of the disease, there is a need for automatic and objective evaluation of movements. Such objective movement assessments would supplement subjective clinical ratings, which are ordinal rather than metric and often show large inter-rater variability. Rather than using a spectral based technique, we rated dynamical features of each individuals’ finger-tapping—one of the items from the unified Parkinson’s disease rating scale (UPDRS) used for rating the severity of the disease—by using data models based on nonlinear delay differential equations (DDEs). The coefficients of the DDEs are then used to assess the severity of the disease.