A Vision-based system for intelligent monitoring of gait poses in dementia

Impairments of gait and balance often progress through the course of dementia, and are associated with increased risk of falls. Regular assessment of gait and balance could therefore be informative in tracking changes in functional status, and identifying individuals at a high risk of falling to allow for preventative measures. We have developed a technology, called AMBIENT, which enables the frequent, accurate, unobtrusive, and cost-effective measurement of gait and balance parameters. The objectives of this project is to improve the technology of the AMBIENT for pose estimation; to replace the depth sensor of AMBEINT with RGB camera; and to concurrently validate the accuracy of the estimated Gait parameters by the camera-based version of the AMBIENT. One important outcome of this study will be the advancement of technology to allow unobtrusive monitoring of changes in mobility in older adults with dementia.

Faculty Supervisor:

Babak Taati

Student:

Elham Dolatabadi

Partner:

Riverview Health Centre Foundation

Discipline:

Engineering - biomedical

Sector:

Information and communications technologies

University:

Program: