Techniques for using VRChat to Replace On-site Experiments

In this paper, we present a technique to conduct on-site laboratory experiments using VRChat, a social Virtual Reality platform. COVID-19 pandemic has created challenges and restrictions on re-searchers in running experiments for Human-Computer Interaction research. Hence, universities and institutions set guidelines for social distancing and encourage people to work from home. Therefore, participants are harder to recruit for experiments that run in a physical laboratory. Our technique uses VRChat as a substitution for running on-site experiments despite social restrictions. We exploit features in VRChat to enable researchers to run experiments with domestically recruited participants. Furthermore, we propose a hassle-free method to retrieve study data. This paper also discusses and offers design considerations to run an on-site experiment using VRChat over a homemade system. © 2022 IEEE.

NL-Beep: A Ranging System between Multiple Smartphones Using Acoustic Sensing in NLOS Environments

In this paper, we describe NL-Beep, which is a novel ranging method between multiple smartphones using acoustic sensing in non-line-of-sight (NLOS) environments. We need to know the distance between people to maintain social distancing because of the COVID-19 pandemic. Acoustic-based ranging methods that use a smartphone built-in speaker and microphone represent one approach to high-accuracy ranging methods. These methods can be used in line-of-sight (LOS) environments where there are no obstacles between the smartphones. However, in daily life, there are usually many obstacles, including pedestrians, and NLOS environments are the norm rather than the exception. Therefore, we propose the NL-Beep system for NLOS environments. To measure the distance between two smartphones without using a direct signal, NL-Beep efficiently uses a reflected signal from the ceiling in an indoor environment. It can also detect LOS and NLOS environments based on the profile of the received signal, and adapt the method used to estimate the distance between the smartphones. In our experiments, we used two smartphones in a room and estimated the distance between them for several placement configurations. In our results, we obtained 90th-percentile errors of less than 11.97 cm for the distances between the smartphones. In this paper, we also mention the effectiveness and limitations of NL-Beep.

GAN-based Face Mask Removal using Facial Landmarks and Pixel Errors in Masked Region

In 2020 and beyond, the opportunities to communicate with others while wearing a face mask have increased. A mask hides the mouth and facial muscles, making it difficult to convey facial expressions to others. In this study, we propose to use generative adversarial networks (GAN) to complete the facial region hidden by the mask. We defined custom loss functions that focus on the errors of the feature point coordinates of the face and the pixels in the masked region. As a result, we were able to generate images with higher quality than existing methods.

Structure of psychological stress during the COVID-19 pandemic and effects of essential oil odor exposure: Poster abstract

This research investigated the psychological stressors during the COVID-19 pandemic and the effects of essential oil odor exposure. In Japan, a stay-at-home restriction order was implemented in May 2020. We sent essential oils to the homes of 30 participants. The participants received emails 5 times a day for 6 days and reported how they felt before and after the essential oil odor exposure. They also reported their circumstances and intentions. Results showed that the vitality and stability levels increased after essential oil odor exposure. Besides, four psychological stress structures were obtained. Some of the participants felt conflicted about balancing housework, childcare, and work. They were the most stressed, and their vitality and stability levels increased considerably. © 2020 Owner/Author.