09/06/2026
COMPUTATIONAL APPROACHES FOR MONITORING AND
AUTOMATED DIAGNOSIS OF PARKINSON’S DISEASE AND MOVEMENT
DISORDERS
Understanding computational approaches used for monitoring, analysis, and
automated assistance in diagnosing Parkinson’s and other movement disorders
using data analysis and Artificial Intelligence. It aims to help the trainees:
▪ Understand basic principles of computational and algorithmic
approaches in medical analysis of motor data.
▪ Know data sources such as motion sensors, wearable devices, and clinical
databases.
▪ Familiarize themselves with machine learning and signal processing
techniques for detection (tremor, bradykinesia, and dyskinesia analysis).
▪ Understand the use of predictive models for evaluating disease
progression and supporting clinical decisions.
▪ Evaluate advantages and limitations of automated diagnosis systems.
▪ Perceive the importance of cooperation between clinical medicine and
computational sciences
The final goal is to develop skills and acquiring knowledge for the application of
computational tools in modern neurological practice.
