Virtual reality, augmented reality and surgical training
Michael Wong
Introduction
Can you imagine a world without technology? What would life be without the internet? No more social media to talk with friends, no more google maps to track a location, no more video games to play after finishing work. Rapid advances in technology have transformed modern society, its uses ranging from multi-functional devices to artificial intelligence to industrial automated systems. We often encounter and use them in our daily lives, in education, work, communication, and entertainment. Technology allows us to carry out tasks with high efficiency and ease, and has helped revolutionize the world. Two of the (related) advanced technologies that are constantly being developed are augmented reality and virtual reality. They have been increasingly used in entertainment and retailing, and they are starting to be used in education and healthcare. During the pandemic, the surge of hospital admissions and patients led to increased demand and increased risk of infection of the NHS staff. The absences of staff reached 20% due to self-isolation and illness. A contributory cause of this shortage of staff is the failure to invest in training. We need to think how surgeon trainees can continue their training without exerting extra pressure on the medical professionals. Augmented reality (AR) and virtual reality (VR) surgeon training may help. In this essay, I compare the traditional training for surgery with AR and VR methods. I also consider how visualization can impact memory, which can affect learning effectiveness.
AR and VR
Augmented reality is when virtual, interactive digital elements merge with the real-world environment (Bonsor, 2018). An example would be the popular gaming application, Pokémon Go, where users capture Pokémon (fictional creatures) distributed globally using AR. The ability to be able to mix aspects of virtual and reality creates an immersive experience. It requires computer vision, 'a field of artificial intelligence that trains computers to interpret and understand the visual world' ( Computer Vision , n.d.), in order to work. Firstly, it scans the area around the user from the depth-sensing camera feed content, which can determine the object's location, distance, and angle. There are also registration tools that assist with the placement of the virtual objects around the user ( How does augmented reality work? 2020). There are two types of AR: marker-based and markerless. Marker-based AR is where the software requires a specific marker to display the virtual image, whereas markerless AR does not require any tracking point and can display virtual objects in different environments.
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