For the first time in almost two decades, nursing researcher Charlene Chu, has received the prestigious National Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant, an award supporting innovation in engineering science.
Chu is an assistant professor at the Lawrence S. Bloomberg Faculty of Nursing, and well known for her program of research that examines the intersections of technology and older adults’ health and well-being. Her new NSERC funded project, will use a multi-modal AI-based sensor system called MAISON (Multimodal AI-based Sensor platform for Older iNdividuals), to better understand how older adults are aging at home.
“We know a lot about older adults who are ill or who have multi-morbidities, but we don’t have much insight into older adults who are ageing in positive and healthy ways” says Chu. “With the rapid advancements in AI and its deployment across multiple sectors, thoughtful examination is required to determine how we can ensure older adults benefit from AI, so that no one is left behind.”
The multi-year NSERC Discovery Grant will fund three interrelated projects including the co-design and deployment of the MAISON app interface that will help Chu and her co-investigator, Dr. Shehroz Khan of UHN’s KITE Toronto Rehabilitation Institute, develop a database that will provide a nuanced understanding of how healthy older adults age actively in their communities. This database will be the first of its kind in Canada to include information on the age, sex, gender, and socioeconomic status of older adults and how this co-relates to their ability to age at home.
The overarching goal Chu says, will be to make this database publicly accessible to researchers from around the world, creating the potential for machine learning models to accurately predict outcomes of active aging, and inform the co-design of new technologies with older adults as key partners in the process.
“These three projects and the app we are creating will be focused on gathering data from people who manage their own health conditions,” says Chu. “We hope to gain a holistic perspective of aging, incorporating feedback from older adults about what they think is important to include in an app that measures their lifestyle and health.”
The sensor system MAISON uses a wearable watch as well as a variety of sensors such as sleep mats, motion detectors, and chair mats to collect information on the wearers physiology including heart rate, blood pressure, and quality of sleep, as well as whether participants are sedentary or active, including how far they can travel from home.
All this detailed information Chu points out, increases the researchers ability to understand how factors like socio-economic status, geographic location, community features, age, sex and gender impact the aging process. This is important, Chu notes because as she has demonstrated in previous research, technology for older adults is often subject to bias or digital ageism, grouping older adults into users of technology for only medication use or chronic health management.
“There is a difference between older adults who are 65 versus those who are 75. We cannot lump together everyone who is 55 and older when we design technology and applications for older adults, but this is what is happening now” says Chu.
The MAISON system and app interface has currently been used to assess and monitor the activity of older adults who have been discharged from inpatient rehabilitation following hip surgery. The technical feasibility of this current project bodes well for Chu and her team.
“Digital ageism partially stems from a lack of data on older adults, including poor labelling and lack of access to technology,” says Chu, “with this project I’m hopeful that we will begin to overcome those barriers.”