Review of Innovative Immersive Technologies for Healthcare Applications

  • Qu Z
  • Lau C
  • Simoff S
  • et al.
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Abstract

Immersive technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), can connect people using enhanced data visualizations to better involve stakeholders as integral members of the process. Immersive technologies have started to change the research on multidimensional genomic data analysis for disease diagnostics and treatments. Immersive technologies are highlighted in some research for health and clinical needs, especially for precision medicine innovation. The use of immersive technology for genomic data analysis has recently received attention from the research community. Genomic data analytics research seeks to integrate immersive technologies to build more natural human-computer interactions that allow better perception engagements. Immersive technologies, especially VR, help humans perceive the digital world as real and give learning output with lower performance errors and higher accuracy. However, there are limited reviews about immersive technologies used in healthcare and genomic data analysis with specific digital health applications. This paper contributes a comprehensive review of using immersive technologies for digital health applications, including patient-centric applications, medical domain education, and data analysis, especially genomic data visual analytics. We highlight the evolution of a visual analysis using VR as a case study for how immersive technologies step, can by step, move into the genomic data analysis domain. The discussion and conclusion summarize the current immersive technology applications' usability, innovation, and future work in the healthcare domain, and digital health data visual analytics.

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APA

Qu, Z., Lau, C. W., Simoff, S. J., Kennedy, P. J., Nguyen, Q. V., & Catchpoole, D. R. (2022). Review of Innovative Immersive Technologies for Healthcare Applications. Innovations in Digital Health, Diagnostics, and Biomarkers, 2(2022), 27–39. https://doi.org/10.36401/iddb-21-04

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