Xinmin Fang, Xingyu Chen, Wenyao Xu, Zhengxiong Li
{"title":"增强虚拟现实:探索一种沉浸式、逼真的虚拟现实护理培训","authors":"Xinmin Fang, Xingyu Chen, Wenyao Xu, Zhengxiong Li","doi":"10.1145/3485730.3492870","DOIUrl":null,"url":null,"abstract":"Virtual Reality (VR) training is an emerging method, which is widely deployed in more and more applications. Compared with traditional physical training and video games-based training, VR training can not only provide a sense of realism and immersion similar to physical training but can also train at any time and place, saving time and money. However, due to some constraints like lacking reflections of the ambient environment, the realism and immersion of VR training are insufficient. Therefore, in this paper, we propose enhanced VR training which senses the ambient environment and reflects them as dynamic unexpected training tasks to solve the above problems.","PeriodicalId":356322,"journal":{"name":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced Virtual Reality: Exploring an Immersive and Realistic Virtual Reality Training for Nursing\",\"authors\":\"Xinmin Fang, Xingyu Chen, Wenyao Xu, Zhengxiong Li\",\"doi\":\"10.1145/3485730.3492870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Virtual Reality (VR) training is an emerging method, which is widely deployed in more and more applications. Compared with traditional physical training and video games-based training, VR training can not only provide a sense of realism and immersion similar to physical training but can also train at any time and place, saving time and money. However, due to some constraints like lacking reflections of the ambient environment, the realism and immersion of VR training are insufficient. Therefore, in this paper, we propose enhanced VR training which senses the ambient environment and reflects them as dynamic unexpected training tasks to solve the above problems.\",\"PeriodicalId\":356322,\"journal\":{\"name\":\"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3485730.3492870\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3485730.3492870","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhanced Virtual Reality: Exploring an Immersive and Realistic Virtual Reality Training for Nursing
Virtual Reality (VR) training is an emerging method, which is widely deployed in more and more applications. Compared with traditional physical training and video games-based training, VR training can not only provide a sense of realism and immersion similar to physical training but can also train at any time and place, saving time and money. However, due to some constraints like lacking reflections of the ambient environment, the realism and immersion of VR training are insufficient. Therefore, in this paper, we propose enhanced VR training which senses the ambient environment and reflects them as dynamic unexpected training tasks to solve the above problems.