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November 2018

New AI-based video system helps seniors stay safe and independent

At a glance
The team

Spxtrm AI with a team of researchers from the University of Alberta’s Faculty of Science, supervised by Professor Irene Cheng.

The challenge

Maintaining independence, safety, and privacy in the home or at care facilities

The solution

Create an in-home video monitoring system 

The outcome

An artificial intelligence system that anonymizes personal information but alerts caregivers in the event of medical distress

What's next

Hire former interns to commercialize the technology

An autonomous intelligence system is helping seniors stay safe both at home and in care facilities, thanks to a collaboration between University of Alberta computing scientists and software technology company Spxtrm AI.

The new tool uses a deep-learning computer vision system and motion-classification algorithms to capture events such as falls in real time, alert caregivers and give health-care professionals the information they need for immediate triage.

The system—developed in part by the Multimedia Research Centre led by Irene Cheng in the Department of Computing Science—transfers real-time video to an autonomous computer vision lockbox. If an event is detected, the system alerts a specified caregiver and provides a redacted video of the event.

“Just-in-time action is needed for falls and other accidents in order to save lives, and only accurate and time-efficient algorithms can deliver real-time solutions,” explained Cheng.

She added that videos are captured continuously and at high resolution.

“It is impossible for humans to monitor these systems and detect the relevant information in real time as effectively as this autonomous system can,” she said.

The system also maintains the privacy of seniors while providing caregivers with important triage information, including the moment of impact after the fall.

“Privacy is a major concern for most seniors,” said Cheng. “Our algorithms are able to extract the necessary information on the fall for analysis without disclosing their physical appearance to human operators and caregivers.”

The research was funded by multi-year Mitacs internships, supporting graduate students and researchers in the research and development of the project.
 


Reposted with permission from the University of Alberta’s Faculty of Science. Author: Katie Willis.

Mitacs thanks the Government of Canada and Alberta Innovates for their support of the Accelerate research internship in this story. Across Canada, the Accelerate program also receives support from the Government of British Columbia, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, the Government of Prince Edward Island, the Government of Quebec, the Government of Saskatchewan, and Research Manitoba.