{"title":"最小增加厌恶(LIA)协议:识别个人对网络晕眩诱因易感性的说明","authors":"Nana Tian;Ronan Boulic","doi":"10.1109/TVCG.2024.3395365","DOIUrl":null,"url":null,"abstract":"This article introduces the Least Increase aversion (LIA) protocol to investigate the relative impact of factors that may trigger cybersickness. The protocol is inspired by the Subjective Matching methodology (SMT) from which it borrows the incremental construction of a richer VR experience, except that the full-blown target experience may cause undesired discomfort. In the first session, the participant briefly encounter all factors at the maximum level. Then in the second session they start with the minimum level of all factors as a Baseline. Subsequently, we expect the participant to minimize their exposure to the most adverse factors. This a pproach ranks the factors from mildest to worst and helps detect individual susceptibility to cybersickness triggers. To validate the applicability of LIA protocol, we further evaluate it with an experiment to identify individual susceptibility to three rotational axes (Yaw, Pitch, and Roll). The findings not only confirm the protocol's capability to accurately discern individual rankings of various factors to cybersickness but also indicate that individual susceptibility is more intricate and multifaceted than initially anticipated.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"31 8","pages":"4156-4168"},"PeriodicalIF":6.5000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10510640","citationCount":"0","resultStr":"{\"title\":\"The Least Increasing Aversion (LIA) Protocol: Illustration on Identifying Individual Susceptibility to Cybersickness Triggers\",\"authors\":\"Nana Tian;Ronan Boulic\",\"doi\":\"10.1109/TVCG.2024.3395365\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article introduces the Least Increase aversion (LIA) protocol to investigate the relative impact of factors that may trigger cybersickness. The protocol is inspired by the Subjective Matching methodology (SMT) from which it borrows the incremental construction of a richer VR experience, except that the full-blown target experience may cause undesired discomfort. In the first session, the participant briefly encounter all factors at the maximum level. Then in the second session they start with the minimum level of all factors as a Baseline. Subsequently, we expect the participant to minimize their exposure to the most adverse factors. This a pproach ranks the factors from mildest to worst and helps detect individual susceptibility to cybersickness triggers. To validate the applicability of LIA protocol, we further evaluate it with an experiment to identify individual susceptibility to three rotational axes (Yaw, Pitch, and Roll). The findings not only confirm the protocol's capability to accurately discern individual rankings of various factors to cybersickness but also indicate that individual susceptibility is more intricate and multifaceted than initially anticipated.\",\"PeriodicalId\":94035,\"journal\":{\"name\":\"IEEE transactions on visualization and computer graphics\",\"volume\":\"31 8\",\"pages\":\"4156-4168\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2024-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10510640\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE transactions on visualization and computer graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10510640/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on visualization and computer graphics","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10510640/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Least Increasing Aversion (LIA) Protocol: Illustration on Identifying Individual Susceptibility to Cybersickness Triggers
This article introduces the Least Increase aversion (LIA) protocol to investigate the relative impact of factors that may trigger cybersickness. The protocol is inspired by the Subjective Matching methodology (SMT) from which it borrows the incremental construction of a richer VR experience, except that the full-blown target experience may cause undesired discomfort. In the first session, the participant briefly encounter all factors at the maximum level. Then in the second session they start with the minimum level of all factors as a Baseline. Subsequently, we expect the participant to minimize their exposure to the most adverse factors. This a pproach ranks the factors from mildest to worst and helps detect individual susceptibility to cybersickness triggers. To validate the applicability of LIA protocol, we further evaluate it with an experiment to identify individual susceptibility to three rotational axes (Yaw, Pitch, and Roll). The findings not only confirm the protocol's capability to accurately discern individual rankings of various factors to cybersickness but also indicate that individual susceptibility is more intricate and multifaceted than initially anticipated.