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21 December 2020 | Story André Damons | Photo Supplied
The KAT Walk mini (Omni Directional Treadmill) used to reduce and eliminate cybersickness.

An officer at the School of Nursing Simulation Laboratory of the University of the Free State (UFS) is aiming to cure or minimise cybersickness in nursing students with a popular virtual reality gaming tool.

Bennie Botha, who is acting as head of the Information, Communication and Simulation Technology at the School of Nursing Simulation Laboratory, developed a virtual environment in which nursing students use immersive virtual reality to perform a simulation scenario. This is part of his master’s degree in Computer Science and Informatics under the supervision of Dr Lizette de Wet and co-supervisor Prof Yvonne Botma.

Botha received his master’s degree with distinction during the UFS virtual graduation in October.

Cybersickness

Botha had found that some people experience cybersickness (almost like motion sickness), which is a significant issue and difficult to address. This he would now try to address with a virtual reality gaming tool – the KAT Walk mini.

According to Botha this technology has never been attempted for health-care education and is mostly used in military and pilot training and is very popular as a gaming platform for hardcore virtual reality gamers.

“To test and provide a possible solution I am going to incorporate the KAT Walk mini (Omni Directional Treadmill – almost like the Ready Player One concept) into which students are strapped and they can physically walk and turn around without the need for large open spaces.

“With this I will try and determine whether it decreases or even eliminates cybersickness due to sensory mismatch while using immersive virtual reality. I wanted to provide possible evidence of what causes cybersickness and want to enable virtual reality as an educational tool, not just for gaming. I think immersive virtual reality has a bright future if the kinks (of which the biggest is cybersickness) can be minimised,” says Botha.

Getting funding

He successfully applied for funding in 2020 and received R150 000.

“I must say I was surprised when I got the approval letter. I thought that due to the economic status it would not go through, but I was really glad when I got the approval as this is my dream and I love working with virtual reality for health care. The grant has made my dream come true, especially considering that this sounds more like something from science fiction,” says Botha.

The project started in November 2017 when Botha first conceptualised the idea and took it to Dr De Wet. He then started it as a masters’ project in 2018 and completed it at the end of 2019.

An equal opportunity for students

Botha says immersive virtual reality gives students more time and a more accessible platform where they can practise their skills as it is easy to use and easy to set up compared to other modalities of simulation. But the biggest task is developing a usable virtual environment that gives students more time to practise and increase their theory and practical integration which is key to providing highly skilled health-care professionals.

“By seeking and possibly implementing the new research, I aim to provide students an equal opportunity to partake in immersive virtual reality simulation as it currently excludes people who are prone to high levels of cybersickness. This means they cannot benefit from the same opportunities as other students do.

“I believe it can help all nursing students in SA and Africa as it is much more cost-effective than high-technology manikins and is easier to set up and access with much less manual input required to make it work (apart from the initial development.).”

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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