A Novel Approach for Movement Evolution Tracking in Parkinson's Disease using Data Analysis and Fuzzy Logic

Abstract

In this paper, a novel approach for the analysis of the movement evolution in patients with Parkinson's disease is presented. The system offers the capabilities of detecting significant degradations in the motor-skills of the patients according to the physiotherapy evaluations, where seven items are measured, including: posture, balance, walking, postural changes, involuntary movements, movement coordination and rigidity. To assess their evolution, two modules are employed: a data analysis module, which uses a clustering algorithm to distribute patients according to their skills and analyses their evolution based on the last three evaluations, and a Decision Support Tool based on a Fuzzy-Logic system, which measures the state of the patient according to the results from the mentioned data analysis module and generates a report per patient including his/her state at each item as well as recommendations considering convenient exercises to be practiced. Thus, the system provides meaningful information to physiotherapists, to support them in the decision-making process.