System Identification and Modeling Approach to Characterizing Rigidity in Parkinson's Disease: Neural and Non-Neural Contributions

摘要

Rigidity (muscle stiffness) is one of the most disabling symptoms in Parkinson's disease (PD). It is clinically defined as an increased resistance to passive movement of a joint. There is a fundamental gap between mechanistic and applied approaches to understanding this symptom. The objective of the current study was to apply a system identification and modeling approach to differentiating the contributions of neural (enhanced muscle reflex) and non-neural (altered mechanical properties of muscle fibers) factors to rigidity. Six patients participated in the study. The wrist joint torque and muscle activities of the wrist muscles were measured during externally induced movements. Each subject was tested in the Off- and On- medication states. System identification and modeling approach was applied to separate the neural from the non-neural component with respect to the overall stiffness. Results show that both factors are responsible for rigidity in PD. Neural-related reflex component is the predominant factor in overall rigidity. Medication therapy decreased the level of reflex component to overall rigidity.