Abstract
The use of multimodal data allows excellent opportunities for human–computer interaction research and novel techniques regarding virtual and augmented reality (VR/AR) experiences. Collecting, coordinating, and synchronizing a large amount of data from multiple VR/AR hardware while maintaining a high framerate can be a daunting task, despite the compelling nature of multimodal data. The Lab Streaming Layer (LSL) is an open-source framework that enables the synchronous collection of various types of multimodal data, unlike existing expensive alternatives. However, despite its potential, this framework has not been fully adopted by the VR/AR research community. In this paper, we present a guideline of the LSL framework’s use in VR/AR research as well as report current trends by performing a comprehensive literature review on the subject. We extract 549 publications using LSL from January 2015 to March 2022. We analyze types of data, displays, and targeted application areas. We describe in-depth reviews of 38 selected papers and provide use of LSL in the VR/AR research community while highlighting benefits, challenges, and future opportunities.
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@article{wang2023scopingreview,
title = {A scoping review of the use of lab streaming layer framework in virtual and augmented reality research},
author = {Qile Wang and Qinqi Zhang and Weitong Sun and Chadwick Boulay and Kangsoo Kim and Roghayeh Leila Barmaki},
doi = {https://doi.org/10.1007/s10055-023-00799-8},
year = {2023},
date = {2023-05-02},
urldate = {2023-05-02},
journal = {Virtual Reality},
abstract = {The use of multimodal data allows excellent opportunities for human–computer interaction research and novel techniques regarding virtual and augmented reality (VR/AR) experiences. Collecting, coordinating, and synchronizing a large amount of data from multiple VR/AR hardware while maintaining a high framerate can be a daunting task, despite the compelling nature of multimodal data. The Lab Streaming Layer (LSL) is an open-source framework that enables the synchronous collection of various types of multimodal data, unlike existing expensive alternatives. However, despite its potential, this framework has not been fully adopted by the VR/AR research community. In this paper, we present a guideline of the LSL framework’s use in VR/AR research as well as report current trends by performing a comprehensive literature review on the subject. We extract 549 publications using LSL from January 2015 to March 2022. We analyze types of data, displays, and targeted application areas. We describe in-depth reviews of 38 selected papers and provide use of LSL in the VR/AR research community while highlighting benefits, challenges, and future opportunities.},
keywords = {2023, geriatric, patient, simulation, vgp, Virtual Human},
pubstate = {published},
tppubtype = {article}
}