Related Experiment Video
Updated: Apr 7, 2026
Author Spotlight: An Alternative Approach to Protein Quantification by Bradford Assay Using a Smartphone
Published on: September 8, 2023
Bridging Accessibility and Precision: Evaluating the Reliability and Validity of a Smartphone-Based Skin Colorimeter
Hongfei Ouyang1,2, Jungang Yang2,3, Xiaoli Ning2,4
1China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Background:
Accurate quantification of skin color is essential for dermatologic research and clinical practice. Conventional methods rely on specialized equipment, trained operators, and high costs. Smartphone-based technologies provide a promising alternative for accessible skin color assessment.
Objective:
To evaluate the reliability and validity of the smartphone-based skin colorimeter application, You Look Good Today (YLGTD), for facial skin color assessment compared with two validated devices, VISIA and DermaLab Combo.
Methods:
A total of 105 Chinese participants with healthy facial skin were enrolled. Cheek skin color measurements were obtained using YLGTD (user self-assessment and physician measurement modes), VISIA, and DermaLab Combo. Inter-rater reliability between YLGTD measurement modes was assessed using intraclass correlation coefficients (ICC) and Bland-Altman analysis. Criterion validity was evaluated using Pearson's correlation coefficients between YLGTD measurements and the reference devices.
Results:
YLGTD demonstrated excellent inter-rater reliability across all parameters (ICC: 0.85-0.95). Bland-Altman analysis showed small biases between the two measurement modes for the L, a, and b (-0.05, 0.18, and -0.99, respectively). For criterion validity, YLGTD in user mode showed strong correlations with DermaLab Combo for L* (r = 0.71), individual typology angle (ITA°, r = -0.81), and chroma (C*, r = 0.78), and moderate correlations for b* (r = 0.59) and hue (h°, r = 0.57). Correlations were consistently stronger in physician mode (L*: r = 0.77; b*: r = 0.75; C*: r = 0.84; ITA°: r = -0.87). VISIA showed a stronger correlation for a* (r = 0.55) but weaker correlations for L* (r = 0.56) and ITA° (r = -0.68) compared with YLGTD.
Conclusion:
The smartphone-based application YLGTD demonstrated excellent reliability and acceptable validity for facial skin color assessment, particularly for pigmentation-related parameters. Its standardized measurement workflow and integrated algorithms enable consistent skin color evaluation across devices and real-world conditions, providing a convenient and cost-effective approach for objective skin color assessment.
