New building assessment tools combined with advanced spatial analysis can be used to improve the design of aged care for people with dementia. A new tool, Plan-EAT, evaluates facility layouts to assess design quality in relation to occupant needs.

Advanced computational techniques (machine learning, agent-based modeling, spatial syntax, fractal analysis) can then be used to improve designs and increase their effectiveness.

Plan-EAT is the first tool suitable for assessment based on architectural floor plans for residential care homes that can be applied at the design stage. By designing facilities rather than retrofitting them, facilities can be truly fit for purpose and improve the well-being of people with dementia who are cared for.

Spatial design for people with dementia

UNSW Professor Michael J. Ostwald, who is leading part of this international project, says people with dementia face particular challenges in interacting with the universe.

“Their independence and well-being can be greatly influenced by the physical environment around them. We need to design better aged care facilities.” Architecture.

More than half (54%) of people living in aged care facilities have dementia. Moreover, the number of Australians with dementia is expected to rise from her 487,500 today to about 1.1 million by 2058, without medical breakthroughs. But “the majority of residential care facilities are designed for people with reduced mobility, not people with dementia,” says Professor Ostwald.

The care people with dementia need is very different from other older people. They include wandering behavior, cognitive problems, and coping with difficulties in daily activities such as communication, toileting, and eating.

Plan-EAT uses evidence-based principles such as safety, size and scale, stimulation reduction, movement and engagement, privacy and social interaction, to assess proposed or existing residential care facilities. Evaluate the floor plan, says Professor Ostwald. These “dementia design principles” reduce symptoms and improve health. However, their implementation remains architecturally difficult.

Read more: Half a million Australians have dementia.That number is expected to triple by 2050

“In a practical sense, Plan-EAT produces a kind of metric that can be used by professional evaluators to measure the properties of a building plan and change the design for the better,” he says. For example, this tool can assess the impact of floorplanning on mobility and security. These are important elements to support care for people with dementia.

Once the design is evaluated, computational analysis can be used to suggest ways to improve the plan, promoting spaces that accommodate a kind of swirling wandering motion that can be safely monitored, he says.

“Furthermore, getting lost can have undesirable consequences. The design prioritizes visibility of the bathroom and kitchen/dining facilities from multiple key points within the facility to keep these everyday functions in check. You need a visual reminder of that,” he says.

“Natural scenery and natural engagement can also improve mental health. This is another factor that can be assessed using Plan-EAT and improved using computer analysis of designs.”

While there is no single formula for such a complex design problem, he says the tool is invaluable in research-based assessments of residential aged care designs.

The research team behind the project includes experts from the University of Stirling, the University of Wollongong, and UNSW Sydney’s Center for Environmental, Dementia and Aging Research, and uses additional computational modeling and optimization techniques to inform its findings. We are investigating how we can complement it. Improve facility design.

Professor Ostwald and his UNSW colleagues, Dr. Ju Hyun Lee and Dr. Michael Dawes, have expertise in both the use of diverse cognitive principles in design and the computational optimization of buildings and urban spaces. The team’s expertise has been applied to a wide range of environments, from office buildings to residences to shopping malls.

“These skills and experience are combined in the Plan-EAT project and offer significant opportunities to improve the design of residential facilities,” says Professor Ostwald. “This is the world’s first approach to creating environments specifically designed for people with dementia.”

Machine learning helps design more livable buildings and cities

Computational design is a data-intensive, technologically advanced approach that helps create smarter, more socially cohesive, and responsive environments. Professor Ostwald’s research uses predictive mathematical models backed by neurophysiology (brain scans and eye movement analysis) to analyze, optimize and understand architectural and urban spaces.

“My team models and predicts how people interact with, understand, and navigate space,” he says. “Over the years, architects and behavioral psychologists have confirmed that certain types of spaces encourage certain types of behavior.”

For example, he says, corridors tend to draw people in, but alcoves encourage small gatherings. Computational modeling predicts typical behavior in space, enabling optimization of designs along desired social or behavioral patterns. It’s a way of understanding invisible design, he says.

Computational design software can analyze small to large designs to optimize walking distance, line of sight, ventilation, access to natural light, and other factors.

“We can overlay computational models on architectural plans and predict where people will hang out or congregate. It can predict where there will be connections. And where crime can occur if there are too many nooks and crannies or too many unobserved or unmonitored areas. can also be predicted.”

Interpreting analysis requires nuance, he says. “Social Connectivity is not about talking to people all the time, which is optimal, but being able to nod to someone across the garden every day.”

By modeling the line of sight, designers can identify where people’s lines of sight intersect. “This makes for an ideal space for a park bench, or a table and seating area. You can sit, which you can do by moving some windows or making them taller or wider,” he says.

Professor Ostwald has consulted on the design and optimization of remote mining communities, correctional facilities, indigenous communities, commercial retail outlets, lodging facilities and recreational districts. He has worked with major industry clients such as BHP Billiton, Stockland Group, Lendlease, Civil & Civic, as well as local and state governments to evaluate commercial and public designs using computational modeling and analysis. .

“For example, we can use fractal geometry and mathematics to predict the level of visual clutter and calculate how complex the environment is. It decreases or increases depending on how you move or walk through space.”

Our understanding of space is refracted through the prism of our experience, he says. There are also cultural differences, which make it both rich and difficult.”

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Plus, we all have slightly different cognitive understandings of space, he says. For example, recent research shows that young millennials are more comfortable with visually complex environments than other age groups. “At a certain age, people prefer less visual complexity,” he says.

Professor Ostwald applies these logics to iconic modern and ancient buildings as well. “I love famous historic and contemporary buildings and enjoy the challenge of applying these complex computational models and mathematics to better understand, for example, a 17th-century building.” he says.

His team focuses primarily on contemporary practical challenges, but draws on research from a variety of disciplines and adapts or develops computational modeling to explore how these lessons can be spatialized or We will consider whether it can be embedded in architecture and find the optimal design method.

It is about creating a legacy of change in the real world. “Our success will be reflected in next-generation legislation governing next-generation buildings,” he says.