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Canadian AI tool seamlessly monitors health of the elderly

New care home tech based on low-power, millimetre-wave radio systems enabled by machine learning and artificial intelligence.

According to NPR.org, there are currently close to 54 million Americans age 65 and older, according to the U.S. Census Bureau, and that number is expected to rise to 95 million by 2060. Source- OSTFlorida, CC SA 3.0.
According to NPR.org, there are currently close to 54 million Americans age 65 and older, according to the U.S. Census Bureau, and that number is expected to rise to 95 million by 2060. Source- OSTFlorida, CC SA 3.0.

Trials have taken place for a new in-home AI tool that monitors the health of elderly residents. Engineers at the University of Waterloo have successfully harnessed artificial intelligence and wireless technology to unobtrusively monitor elderly people in their living spaces and provide early detection of emerging health problems.

The new system can follow an individual’s activities both accurately and continuously, gathering information about the person without the need for the individual to be fitted with a wearable device.

The trials from the Canadian researchers also demonstrated that the technology could alert medical experts about the status of the elderly person and when to step in and provide help. Different activities were tested out, from sleeping, watching TV, eating and with the frequency of bathroom use.

Commenting on this positive application of AI, lead researcher George Shaker, an adjunct associate professor of electrical and computer engineering. said: “After more than five years of working on this technology, we’ve demonstrated that very low-power, millimetre-wave radio systems enabled by machine learning and artificial intelligence can be reliably used in homes, hospitals and long-term care facilities.”

Shaker adds: “An added bonus is that the system can alert healthcare workers to sudden falls, without the need for privacy-intrusive devices such as cameras.”

The hope is that the technology will support overburdened public healthcare systems as they struggle to meet the demands and health requirements of a rapidly growing elderly populations. This build on other wireless, health-based technologies that incorporate machine learning.

While some physical or mental conditions can be anticipated, for any health system it is impossible to track their movements and discover problems 24/7.Hence, the technology represents a major step forward.

In terms of how the technology functions, first, a wireless transmitter sends low-power waveforms across an interior space, such as a long-term care room, apartment or home. Second, as the waveforms bounce off different objects and the people being monitored, they are captured and processed by a receiver. Third, the information is sent to an AI engine which proceeds to decipher the processed data waves for both detection and monitoring applications.

An operating advantage is that the system employs extremely low-power radar technology. This provides portability as well as needing only low power. The device can be mounted simply on a ceiling or by a wall.

The academics will partner with the firm Gold Sentinel in order to commercialize the technology.

The research has been published in the IEEE Internet of Things Journal, titled “AI-Powered Non-Contact In-Home Gait Monitoring and Activity Recognition System Based on mm-Wave FMCW Radar and Cloud Computing.”

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Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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