BioCosMe: lip-based cosmetics with colorimetric biosensors for salivary analysis using deep learning
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Published version
Author(s)
Type
Conference Paper
Abstract
This paper introduces three lip-based product biosensors as novel form factors for health monitoring that display pH levels through color variation. Using the unique properties of lip-based products such as different colors, easy application and reapplication on lips, interaction with saliva, we aim to provide an always-available and non-invasive access to information typically obtained through lab analysis. This paper presents our skin-safe fabrication processes and technical evaluations of a lipstick, lip tint, and lip gloss. We created a mobile app with a Convolutional Neural Network (CNN) model to detect the pH levels. Our dataset involved six users, eight different lighting conditions, three cameras and seven pH levels. The results showed improved detection of pH variations compared to traditional methods. A user study with 11 participants was conducted to evaluate usability. This approach offers a convenient and unexplored form factor for monitoring biochemical information, blending self-expression with health awareness.
Date Issued
2024-10-01
Date Acceptance
2024-10-01
Citation
ISWC '24: Proceedings of the 2024 ACM International Symposium on Wearable Computers, 2024, pp.32-39
ISSN
1550-4816
Publisher
ACM
Start Page
32
End Page
39
Journal / Book Title
ISWC '24: Proceedings of the 2024 ACM International Symposium on Wearable Computers
Copyright Statement
© 2024 Owner/Author. This work is licensed under a Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/).
License URL
Source
ACM International Joint Conference on Pervasive and Ubiquitous Computing / ACM International Symposium on Wearable Computers (UbiComp/ISWC)
Subjects
anthocyanin
biocosmetic interface
biosensors
CNN
color detection
colorimetric biosensors
Computer Science
Computer Science, Cybernetics
Computer Science, Interdisciplinary Applications
cosmetics
deep learning
DENTAL-CARIES
Engineering
Engineering, Electrical & Electronic
Lipstick
PH
Science & Technology
SENSOR
STRESS
SWEAT
Technology
Publication Status
Published
Start Date
2024-10-05
Finish Date
2024-10-09
Coverage Spatial
Melbourne, Australia
Date Publish Online
2024-10-05