Pattern analysis of computer keystroke time series in healthy control and early-stage Parkinson's disease subjects using fuzzy recurrence and scalable recurrence network features

Features extracted from the nonlinear dynamics analysis of the keystroke time series are found to be very effective for machine learning and the properties of the scalable recurrence networks have the potential to be utilized as physiologic markers of the disease.