Development of a Multibody Parametric Model as a Diagnostic and Monitoring Tool for Parkinson Disease Analysis

Parkinson's disease (PD) is the second most common progressive degenerative disease after Alzheimer's disease, and occurs mainly in the population over 65 years of age. This disease, which is usually detected at an advanced stage, depends on a dysfunction of neuronal circuits comprising the motor cortical areas and the basal ganglia, resulting in movement abnormalities. This has a substantial impact on quality of life and requires various strategic treatments, including drug therapy, surgery and rehabilitation. This research work proposes a parametric multibody digital-twin model, developed in the Simulink-Simscape environment, capable of reproducing the posture and movements of PD patients. The model allows an accurate and non-invasive real-time or delayed assessment of patients’ movements, with the aim of identifying the main signs of disease progression at an early stage in order to prevent possible related risk factors and delay disease progression. The proposed method therefore makes it possible to perform, even at a distance, an assessment of the progress and level of severity of the disease, as well as early screening, through the digital monitoring of the maneuvers and clinical tests of the MDS-Unified Parkinson's Disease Rating Scale.