Development of Diagnostic Method of Parkinson’s Disease Based on AI-Assisted Gait Pattern Analysis

 

Project Introduction

 

This project seeks to develop a non-invasive diagnostic method for PD based on AI-assisted gait analysis. By collecting and analysing significant amount of the real gait data collected from both healthy individuals and PD patients, this study will apply advanced signal processing and machine learning techniques to identify key spatiotemporal features indicative of PD. The expected outcome is a high-sensitivity, high-specificity proof-of-concept diagnostic algorithm, which may be embedded into a clinical decision support system or a wearable behaviour monitoring tool, addressing the diagnostic needs of PD in China’s aging population.