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

Sensors (Basel, Switzerland), 2022-06, Vol.22 (12), p.4623 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 by the authors. 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/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22124623 ;PMID: 35746405

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  • Title:
    Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment
  • Author: Moon, Jiyoung ; Jeong, Minho ; Oh, Sangmin ; Laine, Teemu H. ; Seo, Jungryul
  • Subjects: Alzheimers disease ; Avatars ; Avatars (Computer graphics) ; Context ; Context (Linguistics) ; context data collection ; context-awareness ; Data collection ; Design ; embodiment ; Extensibility ; framework ; Galvanic skin response ; Microprocessors ; Performance evaluation ; Physiology ; Sensors ; Social aspects ; Technology application ; Testing ; Unity ; Virtual communities ; Virtual Reality
  • Is Part Of: Sensors (Basel, Switzerland), 2022-06, Vol.22 (12), p.4623
  • 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.
  • Publisher: Basel: MDPI AG
  • Language: English
  • Identifier: ISSN: 1424-8220
    EISSN: 1424-8220
    DOI: 10.3390/s22124623
    PMID: 35746405
  • Source: Open Access: PubMed Central
    Geneva Foundation Free Medical Journals at publisher websites
    ROAD
    ProQuest Central
    DOAJ Directory of Open Access Journals
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