ViTT: Towards a Virtual Reality System that Supports the Learning of Ergonomic Patient Transfers
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While patient transfers are part of nurses’ daily work, the manual transfer of patients can also pose a major risk to nurses’ health. The Kinaesthetics care conception may help nurses to conduct patient transfers more ergonomically. However, existing support to learn the concept is low. We introduce ViTT, a Virtual Reality system to promote the individual, self-directed learning of ergonomic patient transfers based on the Kinaesthetics care conception. The current implementation of ViTT supports a nurse in two phases: (i) instructions for a patient transfer, and (ii) training of the transfer with a virtual patient (based on a physics engine; implementation limited). In contrast to previous work, our approach provides an immersive experience that may allow for the ‘safe’ training of different transfer scenarios—e.g., patients with different impairments—and the study of different parameters that may influence nurses’ learning experience—e.g., the simulation of stress—in the future.
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DÜRR, Maximilian, Daniel SCHWEITZER, Harald REITERER, 2021. ViTT: Towards a Virtual Reality System that Supports the Learning of Ergonomic Patient Transfers. The Adjunct Publication of the 34th Annual ACM Symposium on User Interface Software and Technology. Virtual Event, USA, 10. Okt. 2021 - 14. Okt. 2021. In: NICHOLS, Jeffrey, ed., Ranjitha KUMAR, ed., Michael NEBELING, ed.. UIST '21: The 34th Annual ACM Symposium on User Interface Software and Technology. New York, NY: ACM, 2021, pp. 78-82. ISBN 978-1-4503-8655-5. Available under: doi: 10.1145/3474349.3480234BibTex
@inproceedings{Durr2021Towar-55232, year={2021}, doi={10.1145/3474349.3480234}, title={ViTT: Towards a Virtual Reality System that Supports the Learning of Ergonomic Patient Transfers}, isbn={978-1-4503-8655-5}, publisher={ACM}, address={New York, NY}, booktitle={UIST '21: The 34th Annual ACM Symposium on User Interface Software and Technology}, pages={78--82}, editor={Nichols, Jeffrey and Kumar, Ranjitha and Nebeling, Michael}, author={Dürr, Maximilian and Schweitzer, Daniel and Reiterer, Harald} }
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