The Swinburne University of Technology has teamed up with home care provider Silverchain in the hope of improving the mental well-being of older adults who are receiving home-based aged care.
With an increasing number of Australians receiving aged care services in their homes, combined with the insufficient availability of suitable mental health therapies, the two organisations have created a digital program called e-EMBED which is designed to help older adults who are feeling depressed while living at home.
The program will use digital technology to provide effective psychological strategies to clients receiving home care.
With digital delivery, older adults can use the program on their own and access a range of resources to improve their wellbeing.
Swinburne clinical geropsychologist Professor Sunil Bhar says the latest project builds on the partnership’s previous work that found older people were keen to employ digital technologies to enhance their overall health and wellness.
“The next step is to develop and pilot the digital psychological intervention for depression and evaluate its use in the home context,” Bhar said.
“The design of the final product needs to be carefully planned together with people with depressive symptoms based on their preferences, level of digital literacy, and comfort using technology to improve their health and wellbeing.”
Co-designing digital interventions to reduce symptoms of depression in older Australians receiving home-based aged care is the goal of new research in partnership with Silverchain and Swinburne University of Technology.
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— Silverchain (@SilverChainAUS) April 4, 2023
Silverchain Director of Research Discovery, Professor Tanya Davison said the project marks the first digitally-facilitated mental health intervention designed explicitly for the home-based elderly care environment.
“This program will enable older Australians to access evidence-based treatments and communicate effectively with a mental health clinician in the comfort of their own homes,” Davidson said.
“Our team will develop new tools to tailor digitally enabled approaches to meet the needs and preferences of individual older people.
“This project demonstrates our commitment to be leaders in home care internationally, provide an evidence base for effective care, and to improve the care we offer to more than 115,000 clients each year.”
While the Swinburne and Silverchain work to improve the mental health of older adults, researchers at the University of Waterloo have developed a system that utilises Artificial Intelligence (AI) to non-invasively monitor older adults in their homes, enabling the early detection of potential health issues.
This system tracks an individual’s daily activities in real time, collects critical information without the use of wearable devices, and promptly notifies medical professionals when intervention is required.
It operates by transmitting low-power waveforms through a space, such as a room in a long-term care facility or a private residence, using a wireless transmitter. The receiver captures and processes the reflected waves, which are then analysed by an AI engine for monitoring and detection purposes.
This system utilises low-power radar technology and can be easily installed on a wall or ceiling.
“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,” Dr. George Shaker, an adjunct associate professor of electrical and computer engineering said.
“An added bonus is that the system can alert healthcare workers to sudden falls, without the need for privacy-intrusive devices such as cameras.”
Shaker and his colleagues’ research is particularly important as healthcare systems struggle to cope with the increasing demands of a growing elderly population.
The new system has already been rolled out in a number of long-term care homes.
“Using our wireless technology in homes and long-term care homes can effectively monitor various activities such as sleeping, watching TV, eating and the frequency of bathroom use,” Shaker said.
“Currently, the system can alert care workers to a general decline in mobility, increased likelihood of falls, possibility of a urinary tract infection, and the onset of several other medical conditions.”