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The application of artificial intelligence in the assessment of balance and gait for the patients with Alzheimer's Disease and the implication in the diagnosis and rehabilitation

   School of Medicine

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  Dr W Wang  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Alzheimer’s disease is widely happened for the mid-aged and elderly. The prevalence of Alzheimer’s disease will be increased in the future. The patients with Alzheimer’s disease have different balance and gait patterns from the healthy people. The characteristics of gait after Alzheimer’s disease are slow gait speed, poor endurance, cadence, stride length, and joint angular excursions, and increased mechanical energetic cost.

The early diagnosis of Alzheimer’s disease is still difficult, and little research has done on the direct diagnosis of Alzheimer’s disease patients using motion analysis. The hypothesis of this study is that some of parameters from motion analysis, especially gait, could be useful for the diagnosis of early Alzheimer’s disease. The aim of this project is to investigate whether the patients with Alzheimer’s disease have different balance and gait from the healthy people and which biomechanical parameters could be used to assess the degree of Alzheimer’s disease.

This project will recruit a group of patients with Alzheimer’s disease and to analyze their balance and gait biomechanically, comparing with a group of the healthy as control. The artificial intelligence will be applied in the analysis of motion for the patients. The ultimate aim is to construct a useful method to diagnosis the potential patients at the high risk of Alzheimer’s disease, allowing clinicians to make a good protective means for those before Alzheimer’s disease.

Closing date for applications - September 2023

To enquire - please email Dr Weijie Wang, University of Dundee - [Email Address Removed]

Funding Notes

There is no specific funding for this project. Applicants may find funding sources from their government or possible organisations.
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