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Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment

Virtual Reality (VR) has been adopted as a leading technology for the metaverse, yet most previous VR systems provide one-size-fits-all experiences to users. Context-awareness in VR enables personalized experiences in the metaverse, such as improved embodiment and deeper integration of the real worl...

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Autores principales: Moon, Jiyoung, Jeong, Minho, Oh, Sangmin, Laine, Teemu H., Seo, Jungryul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9228658/
https://www.ncbi.nlm.nih.gov/pubmed/35746405
http://dx.doi.org/10.3390/s22124623
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author Moon, Jiyoung
Jeong, Minho
Oh, Sangmin
Laine, Teemu H.
Seo, Jungryul
author_facet Moon, Jiyoung
Jeong, Minho
Oh, Sangmin
Laine, Teemu H.
Seo, Jungryul
author_sort Moon, Jiyoung
collection PubMed
description Virtual Reality (VR) has been adopted as a leading technology for the metaverse, yet most previous VR systems provide one-size-fits-all experiences to users. Context-awareness in VR enables personalized experiences in the metaverse, such as improved embodiment and deeper integration of the real world and virtual worlds. Personalization requires context data from diverse sources. We proposed a reusable and extensible context data collection framework, ManySense VR, which unifies data collection from diverse sources for VR applications. ManySense VR was implemented in Unity based on extensible context data managers collecting data from data sources such as an eye tracker, electroencephalogram, pulse, respiration, galvanic skin response, facial tracker, and Open Weather Map. We used ManySense VR to build a context-aware embodiment VR scene where the user’s avatar is synchronized with their bodily actions. The performance evaluation of ManySense VR showed good performance in processor usage, frame rate, and memory footprint. Additionally, we conducted a qualitative formative evaluation by interviewing five developers (two males and three females; mean age: 22) after they used and extended ManySense VR. The participants expressed advantages (e.g., ease-of-use, learnability, familiarity, quickness, and extensibility), disadvantages (e.g., inconvenient/error-prone data query method and lack of diversity in callback methods), future application ideas, and improvement suggestions that indicate potential and can guide future development. In conclusion, ManySense VR is an efficient tool for researchers and developers to easily integrate context data into their Unity-based VR applications for the metaverse.
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spelling pubmed-92286582022-06-25 Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment Moon, Jiyoung Jeong, Minho Oh, Sangmin Laine, Teemu H. Seo, Jungryul Sensors (Basel) Article Virtual Reality (VR) has been adopted as a leading technology for the metaverse, yet most previous VR systems provide one-size-fits-all experiences to users. Context-awareness in VR enables personalized experiences in the metaverse, such as improved embodiment and deeper integration of the real world and virtual worlds. Personalization requires context data from diverse sources. We proposed a reusable and extensible context data collection framework, ManySense VR, which unifies data collection from diverse sources for VR applications. ManySense VR was implemented in Unity based on extensible context data managers collecting data from data sources such as an eye tracker, electroencephalogram, pulse, respiration, galvanic skin response, facial tracker, and Open Weather Map. We used ManySense VR to build a context-aware embodiment VR scene where the user’s avatar is synchronized with their bodily actions. The performance evaluation of ManySense VR showed good performance in processor usage, frame rate, and memory footprint. Additionally, we conducted a qualitative formative evaluation by interviewing five developers (two males and three females; mean age: 22) after they used and extended ManySense VR. The participants expressed advantages (e.g., ease-of-use, learnability, familiarity, quickness, and extensibility), disadvantages (e.g., inconvenient/error-prone data query method and lack of diversity in callback methods), future application ideas, and improvement suggestions that indicate potential and can guide future development. In conclusion, ManySense VR is an efficient tool for researchers and developers to easily integrate context data into their Unity-based VR applications for the metaverse. MDPI 2022-06-19 /pmc/articles/PMC9228658/ /pubmed/35746405 http://dx.doi.org/10.3390/s22124623 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Moon, Jiyoung
Jeong, Minho
Oh, Sangmin
Laine, Teemu H.
Seo, Jungryul
Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment
title Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment
title_full Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment
title_fullStr Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment
title_full_unstemmed Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment
title_short Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment
title_sort data collection framework for context-aware virtual reality application development in unity: case of avatar embodiment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9228658/
https://www.ncbi.nlm.nih.gov/pubmed/35746405
http://dx.doi.org/10.3390/s22124623
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