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The method for quantified analysis and pattern visualization for eye blinking using high-frame-rate video.

Woon-Hee Lee1, Jongmo Seo1,2, Jeong-Min Hwang2,3

  • 1Department of Electrical and Computer Engineering, Seoul National University, 08826 Seoul, Republic of Korea.

Biomedical Engineering Letters
|November 24, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a non-contact method using high-frame-rate videos to analyze eye blinking patterns. The technique quantifies eyelid movements, classifying different blink types for broader applications.

Keywords:
Blinking patternBlinking visualizationEye blinkingQuantified analysis

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Area of Science:

  • Biomedical Engineering
  • Computer Vision
  • Human-Computer Interaction

Background:

  • Conventional eye blink analysis often relies on bio-signals, facing spatial and situational limitations.
  • Non-contact methods are desirable for user comfort and broader applicability in various environments.

Purpose of the Study:

  • To propose and validate a novel visualization and analysis method for eye blinking patterns using high-frame-rate videos.
  • To enable quantitative analysis of eyelid movements without specialized equipment.
  • To classify and detect specific eye blinking patterns, including incomplete and consecutive blinks.

Main Methods:

  • Utilizing high-frame-rate videos captured with a standard camera.
  • Extracting relevant eye blinking sequences, excluding eyelid flutters and microsleeps.
  • Evaluating upper eyelid shape and position changes during blinks.
  • Visualizing each blink as a single image and calculating various parameters.
  • Segmenting blink sequences into phases for detailed pattern classification.

Main Results:

  • Quantitative analysis of eyelid movements was achieved in 80 volunteers.
  • Various parameters related to eye blinking were successfully calculated.
  • Different eye blinking patterns were visualized as graph images.
  • Incomplete and consecutive eye blinking patterns were defined and detected.
  • The method demonstrated non-contact measurement capabilities in ordinary environments.

Conclusions:

  • The proposed high-frame-rate video analysis method offers a non-contact, versatile approach to studying eye blinking.
  • Quantitative eye blink data from videos provide richer information compared to traditional bio-signals.
  • This technique overcomes limitations of conventional methods and has potential for wide-ranging applications.