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Quantitatively plotting the human face for multivariate data visualisation illustrated by health assessments using

Wang Hongwei1, Liu Hui2

  • 1Department of Computer Science, Dalian Medical University, Dalian 116044, China.

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This study introduces a novel 3Z facial data visualization system. This innovative approach effectively distinguishes individuals with poor health status from healthy controls using facial parameter analysis.

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Area of Science:

  • Biomedical Engineering
  • Data Visualization
  • Medical Imaging

Background:

  • Assessing multivariate data impacts on human health is complex.
  • Traditional methods may not capture subtle health-related changes effectively.

Purpose of the Study:

  • To introduce a novel data visualization system using human facial plotting.
  • To observe the comprehensive effects of multivariate data on facial morphology.

Main Methods:

  • Developed a program using Graphics Device Interface (GDI+) on Visual Studio.NET.
  • Recorded facial image parameters (cropping, rotation) and generated new images based on Z-values.
  • Utilized clinical laboratory parameters from senile individuals, glaucoma patients, and fatty liver patients.

Main Results:

  • Facial feature rotation demonstrated consistent deformation patterns.
  • Individual abnormalities caused slightly greater deformation than simultaneous ones.
  • Significant facial changes were observed in patient groups compared to controls.

Conclusions:

  • The 3Z facial data visualization system effectively differentiates individuals with poor health from healthy ones.
  • The combined effect of multivariate data on facial appearance may not be simply additive.