Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

5.7K
At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
5.7K
Spectrophotometry: Introduction01:16

Spectrophotometry: Introduction

3.0K
Spectrophotometry is the quantitative measurement of the absorption, reflection, diffraction, or transmission of electromagnetic radiation through a material as a function of the intensity and wavelength of the radiation. A spectrophotometer is a device used to measure the change in the radiation intensity caused by its interaction with the material.
The essential components of a spectrophotometer include a source of electromagnetic radiation, a slot for placing a material to be analyzed, and a...
3.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Clinical Applications of Biophysical Stimuli Technologies for Bone Healing.

Annals of biomedical engineering·2026
Same author

An Optical Sensor for Measuring In-Plane Linear and Rotational Displacement.

Sensors (Basel, Switzerland)·2025
Same author

An Optical Sensor for Measuring Displacement between Parallel Surfaces.

Sensors (Basel, Switzerland)·2024
Same author

An Optoelectronics-Based Compressive Force Sensor with Scalable Sensitivity.

Sensors (Basel, Switzerland)·2023
Same author

Magnetoelastic Monitoring System for Tracking Growth of Human Mesenchymal Stromal Cells.

Sensors (Basel, Switzerland)·2023
Same author

<i>In vitro</i>magnetohydrodynamics system for modulating cell migration.

Biomedical physics & engineering express·2023
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jun 6, 2025

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis
10:35

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis

Published on: October 17, 2016

7.8K

Skin Phototype Classification with Machine Learning Based on Broadband Optical Measurements.

Xun Yu1, Keat Ghee Ong1,2, Michael Aaron McGeehan1,2

  • 1Department of Bioengineering, Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, Eugene, OR 97403, USA.

Sensors (Basel, Switzerland)
|November 27, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an optical sensor and K-means algorithm for objective skin phototype classification, improving upon the subjective Fitzpatrick scale. This technology offers better resolution for diverse skin tones, potentially reducing dermatological care disparities.

Keywords:
Fitzpatrick skin typeK-means clusteringdermatologymachine learningskin optical propertiesskin type classification

More Related Videos

Characterization of Biological Absorption Spectra Spanning the Visible to the Short-Wave Infrared
07:38

Characterization of Biological Absorption Spectra Spanning the Visible to the Short-Wave Infrared

Published on: January 10, 2025

1.1K
Precision Implementation of Minimal Erythema Dose MED Testing to Assess Individual Variation in Human Inflammatory Response
06:31

Precision Implementation of Minimal Erythema Dose MED Testing to Assess Individual Variation in Human Inflammatory Response

Published on: October 3, 2019

8.6K

Related Experiment Videos

Last Updated: Jun 6, 2025

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis
10:35

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis

Published on: October 17, 2016

7.8K
Characterization of Biological Absorption Spectra Spanning the Visible to the Short-Wave Infrared
07:38

Characterization of Biological Absorption Spectra Spanning the Visible to the Short-Wave Infrared

Published on: January 10, 2025

1.1K
Precision Implementation of Minimal Erythema Dose MED Testing to Assess Individual Variation in Human Inflammatory Response
06:31

Precision Implementation of Minimal Erythema Dose MED Testing to Assess Individual Variation in Human Inflammatory Response

Published on: October 3, 2019

8.6K

Area of Science:

  • Biomedical Optics
  • Dermatology
  • Machine Learning in Healthcare

Background:

  • The Fitzpatrick Skin Phototype Classification (FSPC) scale is a standard but has limitations including underrepresentation of darker skin tones and subjectivity.
  • These limitations can lead to disparities in dermatological care, misdiagnosis of wound healing, and underestimation of disease severity for individuals with darker skin.
  • Objective and high-resolution skin typing methods are needed to address these disparities.

Purpose of the Study:

  • To develop and validate an objective method for skin phototype classification using optical sensing and machine learning.
  • To compare the performance of the developed algorithm against the traditional FSPC scale.
  • To explore optimization of the method across different spectral bands for clinical applications.

Main Methods:

  • Development of an optical sensor measuring light reflectance from 410-940 nm.
  • Application of an unsupervised K-means clustering algorithm for skin phototype classification using broadband optical data.
  • Comparison of algorithm-based classification with human FSPC assessment in a diverse cohort (n=30).

Main Results:

  • The FSPC scale showed limited differentiation between closely related skin phototypes (e.g., I vs. II) but could distinguish broad ranges (e.g., I vs. VI).
  • The K-means algorithm demonstrated superior differentiation across a wider range of skin phototypes and wavelengths.
  • The optical sensor and algorithm approach provided better classification resolution, proving quantifiable and reproducible.

Conclusions:

  • An optical sensor combined with a K-means algorithm offers a more objective, reproducible, and higher-resolution method for skin phototype classification than the FSPC scale.
  • This technology has the potential to mitigate dermatological care disparities by providing accurate skin typing across the full spectrum of skin tones.
  • Further optimization for specific spectral bandwidths can enhance clinical utility and diagnostic accuracy in dermatology.