AI technology to improve care for people with dementia
After completing a Master of Research in IT for aged care, student Zhenyu Zhang participated in a research on evaluating the impact of implementing a new wireless tele-monitoring system for urinary continence management of nursing home residents.
Her interest drove her to continue further PhD studies on application of AI technology to improve care for people with dementia.
Using technology to track behavioural incidents and responses of personal care workers, gave Zhenyu newfound respect for the commitment of nursing staff for their patients and the daily lives of residents.
“To date, a large volume of data about managing agitated behaviour of people with dementia have been recorded in nursing homes. However, the valuable information in these data sets have not been effectively used to guide person-centred care.” she said.
Zhenyu’s PhD project explores the application of artificial intelligence (AI) technologies to reuse these data. To achieve this, first we need to code clinical knowledge in a machine-readable format using a specific computer dictionary – ontology. Therefore, Zhenyu developed a machine-readable “Dementia-Related Agitation Non-Pharmacological Treatment Ontology” called DRANPTO.
DRANPTO provides a knowledge base to develop information systems that can help nurses and carers to deliver person-centred care for people with dementia.
The development of DRANPTO is published in the journal Alzheimer’s & Dementia: Translational Research & Clinical Interventions under the title “Developing an ontology for representing the domain knowledge specific to non-pharmacological treatment for agitation in dementia”.
Zhenyu is sponsored by a joint scholarship ‘Eric Abrahams PhD Scholarship’ from Australian Rotary Health, the Rotary Club of Woy Woy, and University of Wollongong; and supervised by Associated Professor Ping Yu, Doctor Sim Kim Lau from School of Computing and Information Technology, Doctor Rita Chang from School of Nursing, and Professor Chao Deng from School of Medicine. The study is also supported by international collaborators Professor Cui Tao and Professor Ning Wang.