TY - GEN
T1 - The Smell Engine
T2 - 29th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2022
AU - Bahremand, Alireza
AU - Manetta, Mason
AU - Lai, Jessica
AU - Lahey, Byron
AU - Spackman, Christy
AU - Smith, Brian H.
AU - Gerkin, Richard C.
AU - Likamwa, Robert
N1 - Funding Information:
This research was supported by the NSF Next Generation Networks for Neuroscience Program (Award 2014217), the ASU Interplanetary Initiative, the ASU School of Life Sciences, the ASU School of Arts, Media and Engineering, the ASU School for the Future of Innovation in Society, the ASU Mayo Clinic Seed Grant, and National Institutes of Health (NIDCD R01DC017757 and R01DC018455, NINDS U19NS112953). Special thanks to Dylan Kerr for the design and build of the headset nose clamp.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Mimicking physical odor sensations virtually can present users with a real-time odor synthesis that approximates what users would smell in a virtual environment, e.g., as they walk around in virtual reality. To this end, we devise a Smell Engine that includes: (i) a Smell Composer framework that allows developers to configure odor sources in virtual space, (ii) a Smell Mixer that dynamically estimates the odor mix that the user would smell, based on diffusion models and relative odor source distances, and (iii) a Smell Controller that coordinates an olfactometer to physically present an approximation of the odor mix to the user's mask from a set of odorants channeled through controllable flow valves. Through a three-part user study, we found that the Smell Engine can help measure a subject's olfactory detection threshold and improve their ability to precisely localize odors in the virtual environment, as compared to existing trigger-based solutions.
AB - Mimicking physical odor sensations virtually can present users with a real-time odor synthesis that approximates what users would smell in a virtual environment, e.g., as they walk around in virtual reality. To this end, we devise a Smell Engine that includes: (i) a Smell Composer framework that allows developers to configure odor sources in virtual space, (ii) a Smell Mixer that dynamically estimates the odor mix that the user would smell, based on diffusion models and relative odor source distances, and (iii) a Smell Controller that coordinates an olfactometer to physically present an approximation of the odor mix to the user's mask from a set of odorants channeled through controllable flow valves. Through a three-part user study, we found that the Smell Engine can help measure a subject's olfactory detection threshold and improve their ability to precisely localize odors in the virtual environment, as compared to existing trigger-based solutions.
KW - Computer systems organization
KW - Human-centered computing
KW - Interactive systems and tools
KW - Sensors and actuators
UR - http://www.scopus.com/inward/record.url?scp=85129396762&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85129396762&partnerID=8YFLogxK
U2 - 10.1109/VR51125.2022.00043
DO - 10.1109/VR51125.2022.00043
M3 - Conference contribution
AN - SCOPUS:85129396762
T3 - Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2022
SP - 241
EP - 249
BT - Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 March 2022 through 16 March 2022
ER -