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The Automated Monitoring of Gait as a Predictor of Fall Risk

Principal Investigator:
  • Babak Taati, Toronto Rehabilitation Institute
  • Alzheimer's Association

Project Overview

People with dementia are at a high risk for falls which are a leading cause of injury and can contribute to loss of independence and quality of life. Many falls could be prevented if there was a way to predict an individual’s likelihood of falling and offer interventions to reduce this risk. New research suggests that subtle changes in a person’s gait, or manner of walking, may be linked to the risk of fall in people with dementia. A tool that can detect these changes could be used to monitor people with dementia and reduce their risk of injury. Babak Taati, Ph.D., and colleagues developed a tool (ambient mobility, balance, and gait evaluation and monitoring technology; AMBIENT) that measures walking patterns using a wall-mounted camera. AMBIENT can monitor the mobility of people with dementia in a way that is accurate, non-intrusive and cost-effective. The researchers can use this technology to assess walking patterns and stability of older adults with dementia as they move about their environment. The results of this study will provide the information needed for the researchers to conduct larger human clinical trials using AMBIENT to detect and predict fall risk. This novel technology has the potential to prevent injury and prolong independence and quality of life for individuals with dementia.

Source: https://www.alz.org/research/for_researchers/grants/funded-studies-details?FundedStudyID=2047