Skinly: A novel handheld IoT device for validating biophysical skin characteristics.

artificial intelligence field test internet of things machine learning mobile application non-invasive measurement skin physiological properties

Journal

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
ISSN: 1600-0846
Titre abrégé: Skin Res Technol
Pays: England
ID NLM: 9504453

Informations de publication

Date de publication:
Mar 2024
Historique:
received: 22 02 2024
accepted: 26 02 2024
medline: 29 2 2024
pubmed: 29 2 2024
entrez: 29 2 2024
Statut: ppublish

Résumé

Recent advancements in artificial intelligence have revolutionized dermatological diagnostics. These technologies, particularly machine learning (ML), including deep learning (DL), have shown accuracy equivalent or even superior to human experts in diagnosing skin conditions like melanoma. With the integration of ML, including DL, the development of at home skin analysis devices has become feasible. To this end, we introduced the Skinly system, a handheld device capable of evaluating various personal skin characteristics noninvasively. Equipped with a moisture sensor and a multi-light-source camera, Skinly can assess age-related skin parameters and specific skin properties. Utilizing state-of-the-art DL, Skinly processed vast amounts of images efficiently. The Skinly system's efficacy was validated both in the lab and at home, comparing its results to established "gold standard" methods. Our findings revealed that the Skinly device can accurately measure age-associated parameters, that is, facial age, skin evenness, and wrinkles. Furthermore, Skinly produced data consistent with established devices for parameters like glossiness, skin tone, redness, and porphyrin levels. A separate study was conducted to evaluate the effects of two moisturizing formulations on skin hydration in laboratory studies with standard instrumentation and at home with Skinly. Thanks to its capability for multi-parameter measurements, the Skinly device, combined with its smartphone application, holds the potential to replace more expensive, time-consuming diagnostic tools. Collectively, the Skinly device opens new avenues in dermatological research, offering a reliable, versatile tool for comprehensive skin analysis.

Sections du résumé

BACKGROUND BACKGROUND
Recent advancements in artificial intelligence have revolutionized dermatological diagnostics. These technologies, particularly machine learning (ML), including deep learning (DL), have shown accuracy equivalent or even superior to human experts in diagnosing skin conditions like melanoma. With the integration of ML, including DL, the development of at home skin analysis devices has become feasible. To this end, we introduced the Skinly system, a handheld device capable of evaluating various personal skin characteristics noninvasively.
MATERIALS AND METHODS METHODS
Equipped with a moisture sensor and a multi-light-source camera, Skinly can assess age-related skin parameters and specific skin properties. Utilizing state-of-the-art DL, Skinly processed vast amounts of images efficiently. The Skinly system's efficacy was validated both in the lab and at home, comparing its results to established "gold standard" methods.
RESULTS RESULTS
Our findings revealed that the Skinly device can accurately measure age-associated parameters, that is, facial age, skin evenness, and wrinkles. Furthermore, Skinly produced data consistent with established devices for parameters like glossiness, skin tone, redness, and porphyrin levels. A separate study was conducted to evaluate the effects of two moisturizing formulations on skin hydration in laboratory studies with standard instrumentation and at home with Skinly.
CONCLUSION CONCLUSIONS
Thanks to its capability for multi-parameter measurements, the Skinly device, combined with its smartphone application, holds the potential to replace more expensive, time-consuming diagnostic tools. Collectively, the Skinly device opens new avenues in dermatological research, offering a reliable, versatile tool for comprehensive skin analysis.

Identifiants

pubmed: 38419420
doi: 10.1111/srt.13613
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e13613

Informations de copyright

© 2024 Beiersdorf AG. Skin Research and Technology published by John Wiley & Sons Ltd.

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Auteurs

Maria Del Pilar Bonilla Tobar (MDPB)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Sven Clemann (S)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Ralf Hagens (R)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Sonja Pagel-Wolff (S)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Stefan Hoppe (S)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Peter Behm (P)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Felicia Engelhard (F)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Maria Langhals (M)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Stefan Gallinat (S)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Alex Zhavoronkov (A)

Insilico Medicine, Hong Kong Science Park, Hong Kong, Hong Kong.

Anastasia Georgievskaya (A)

Haut.ai, Tallin, Estonia.

Konstantin Kiselev (K)

Haut.ai, Tallin, Estonia.

Timur Tlyachev (T)

Haut.ai, Tallin, Estonia.

Sören Jaspers (S)

Research and Development, Beiersdorf AG, Hamburg, Germany.

Classifications MeSH