Please join us for talks by Dr Caleb Ferguson on wearable cardiac technologies for older adults, followed by Dr Quang Vinh Ngyuen on genomic data anlaytics with virtual reality.
Zoom ID: 986 9057 6845
Topic: Patient and clinician perspectives on the design and adoption of wearable cardiac technologies for older adults
Speaker: Dr Caleb Ferguson, Senior Research Fellow at the Western Sydney Nursing & Midwifery Research Centre (WSNMRC)
Abstract: New wearable devices (for example, AliveCor or Zio patch) offer promise in detecting arrhythmia and monitoring cardiac health status, among other clinically useful parameters in older adults. However, the clinical utility and usability from the perspectives of clinicians and patients are largely unexplored. A series of studies aimed to explore clinician and patient perspectives on the use of wearable cardiac monitoring technology for older adults was undertaken. There remain pitfalls related to the design of wearable cardiac technology for older adults that present clinical challenges. These likely negatively impact the adoption in routine clinical care. Partnering with clinicians and patients in the co-design of new wearable cardiac monitoring technologies is critical. This study was funded through a SPHERE Age & Ageing CAG seed grant, collaborators include Dr Caleb Ferguson, A/Prof Paul Breen, A/Prof Gaetano Gargiulo, Prof Peter Macdonald, A/Prof Sally Inglis, A/Prof Louise Hickman, Victoria Byiers, and clinical collaborators at Sutherland Hospital, St Vincent’s Hospital and Blacktown Hospital.
Topic: Enabling Genomic Data Analytics with Virtual Reality
Speaker: Dr Quang Vinh Nguyen, Senior Lecturer in Visual Analytics and The Director of Academic Program - Post-Graduate ICT at the School of Computer, Data and Mathematical Sciences
Abstract: Virtual Reality (VR) environment has gained gradual traction in data analytics thanks to reduced distraction, increased space, and natural interactions integration. VR technologies could provide significant improvement on scientific genomic data visualisation and interpretation, especially when merged with machine learning models. This presentation provides an overview of how VR has been used in genomic data analytics. In the project, we learnt from our existing research work on visualisations and machine learning, extracting essential requirements based on feedback from end-users, such as clinicians and researchers, to enhance the genomic data analytics in virtual and mixed reality environments.
The zoom ID is: 986 9057 6845. Link to zoom https://uws.zoom.us/j/98690576845