Functional MRI for post-stroke rehabilitation

Motor impairment is a common symptom after stroke and recovery of motor function is important for regaining the patient’s independence in activities of daily living. Being able to predict motion recovery and outcomes soon after stroke could support clinicians, patients and families to set proper goals for rehabilitation and appropriate plans of time and resource allocation. In this project, multimodal medical imaging data such as MRI and/or CT will be used to predict the recovery of upper limb function after stroke. The deep learning algorithms will be developed to predict the post stroke recovery based on the quantitative imaging biomarkers derived from the multimodal medical images.

The proposed project focuses on using advanced MRI technology and augmented reality (AR) to improve stroke recovery. By analyzing MRI scans, the research aims to predict how well patients will regain motor function after a stroke. The project will also develop and test an AR-based app to help patients with spatial neglect, a common post-stroke condition. This collaboration between Memorial University and the University of Auckland will enhance research capabilities at both institutions, foster international partnerships, and provide valuable insights that could lead to better stroke rehabilitation methods.

Faculty Supervisor:

Sam Nakhla

Student:

Partner:

University of Auckland

Discipline:

Engineering

Sector:

Biotechnology; Health and Related Sciences & Technology; Artificial Intelligence

University:

Memorial University of Newfoundland

Program: