Preventing falls: Researchers improve sensor system for identifying high-risk seniors

July 27, 2017

Dr. Edward Lemaire has co-developed a more accurate way for healthcare providers to predict falls in older people. Falls are the leading cause of injury among older Canadians, but are often preventable through changes in health, fitness and in the home environment. In the study published in Sensors, older individuals wore accelerometer sensors on their legs and pelvis during a 6-minute walking test. The researchers’ found that when a person made multiple turns, artificial intelligence analysis of the sensor data gave a more accurate prediction of their fall risk than if they had done typical straight walking. This is because people at risk of falling are often less stable when navigating turns, which is picked up by the sensors. Dr. Lemaire’s team plans to add this method into their TOHRC Walk Test smartphone app to allow clinicians to have immediate fall risk prediction for their patients.

Authors: Dylan Drover, Jennifer Howcroft, Jonathan Kofman, Edward Lemaire.

Funders: Natural Sciences and Engineering Research Council of Canada

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