Recognizing Parkinsonian Gait Pattern

Parkinson’s Disease (PD) is one of the typical movement disorder diseases among elderly people, which has a serious impact on their daily lives. In this project, we propose a novel computation framework to recognize gait patterns in patients with PD. The key idea of our approach is to distinguish gait patterns in PD patients from healthy individuals by accurately extracting gait features which capture all the three aspects of movement functions. We evaluate the framework using an open dataset that contains real plantar pressure data of 93 PD patients and 72 healthy individuals. Experimental results demonstrate that our framework significantly outperforms the four baseline approaches.

This work appears in ACM Transactions on Intelligent Systems and Technology.

Tao Gu
Tao Gu
Email: firstname dot lastname AT
Phone: +61-2-9850-4357
Address: Room 267, 4 Research Park Drive, North Ryde, NSW 2109, Australia

My research interests include Internet of Things, Ubiquitous Computing, Mobile Computing, Embedded AI, Wireless Sensor Networks, and Big Data Analytics.