Computer Science > Human-Computer Interaction
[Submitted on 4 Sep 2023]
Title:Intranasal Chemosensory Lateralization Through the Multi-electrode Transcutaneous Electrical Nasal Bridge Stimulation
View PDFAbstract:Numerous studies have been conducted on display techniques for intranasal chemosensory perception. However, a limited number of studies have focused on the presentation of sensory spatial information. To artificially produce intranasal chemosensory spatial perception, we focused on a technique to induce intranasal chemosensation by transcutaneous electrical stimulation between the nasal bridge and the back of the neck. Whether this technique stimulates the trigeminal nerve or the olfactory nerve remains debatable; if this method stimulates the trigeminal nerve, the differences in the amount of stimulation to the left and right trigeminal branches would evoke lateralization of intranasal chemosensory perception. Therefore, we propose a novel method to lateralize intranasal chemosensation by selectively stimulating the left or right trigeminal nerve branches through the shifting of an electrode on the nasal bridge to the left or right. Finite element simulations reveal that electrical stimulation applied between the electrodes on the left/right nasal bridge and the back of the neck results in the construction of a high current density area on the left/right branch of the trigeminal nerve. The results of two psychophysical experiments reveal that intranasal chemosensation can be lateralized by using the proposed method. The results of our experiment also suggest that lateralization is not the result of electrically induced tactile sensation of the skin surface but rather due to the distribution of stimuli to the trigeminal nerves. To the best of our knowledge, this study is the first successful lateralization of intranasal chemosensation that utilizes an easy-to-apply method without involving nostril blocking.
Current browse context:
cs.HC
Change to browse by:
References & Citations
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.