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Automatic Gait Recognition and Other Activities of Daily Living in Older Adults.

  • School: School of Science and Technology
  • Starting: 2022 / 2023
  • Funding: UK student / EU student (non-UK) / International student (non-EU) / Fully-funded

Overview

Older age is associated with an increased risk of poor physical function, cognitive decline and an increased risk of diseases. Successful ageing is a multidimensional phenomenon that depends on several individual and environmental factors. Successful ageing is thought to be closely related to the preservation of autonomy, and the ability to function independently in all Activities of Daily Living (ADLs).

Reduction in ADLs is related to an increased risk of diseases and a decrease in functional health. Limited research has shown the connection between mobility and autonomy in ADLs. However, optimal mobility, especially walking is central to healthy ageing. This suggests that changes in mobility in older adults may directly affect older adults undertaking ADLs. An individual’s capability to perform ADLs can vary considerably over time. Failure to detect changes early could expose older adults to interventions and strategies offering little or no improvement causing undue stress and wasting resources. Detecting an incline in mobility during onset may allow for an intervention to be implemented with the possibility to prevent further decline or even reverse functionality. This project will aim to develop methods which may allow incline in mobility and ADLs to be detected during the onset and thus allow an early treatment recommendation to be made.

Entry qualifications

- Essential undergraduate degree or MSc in a field related to biomechanics, physiotherapy, rehabilitation engineering, medical engineering, sports science, computer science or related fields.

- Desirable to have experience in using a code language (e.g. MATLAB, R or Python).

- Desirable biomechanics-related skills (motion capture, force plates, IMU).

How to apply

For any questions, please email maria.bisele@ntu.ac.uk

https://www.ntu.ac.uk/staff-profiles/science-technology/maria-bisele

The application deadline for this project is 9th October 2022.

Fees and funding

Fully funded PhD at UK rates. International students are welcome to apply, however, the difference in fees must be covered.

Guidance and support

Find out about guidance and support for PhD students.

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Maria Bisele