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

## TL;DR

This paper introduces a new non-contact method using high-frame-rate videos to analyze and visualize eye blinking patterns in ordinary environments.

## Contribution

A novel non-contact method for quantifying and visualizing eye blinking patterns using high-frame-rate video data is proposed.

## Key findings

- The method successfully quantitatively analyzed eyelid movements in 80 volunteers.
- Incomplete and consecutive eye blinking patterns were defined and detected using visualized graph images.
- Video-based analysis provides more detailed information than conventional bio-signal methods.

## Abstract

This study proposes a visualization and analysis method for eye blinking pattern using high-frame-rate videos. The high-frame-rate video clips for visualization are taken using a camera without additional equipment. The partial video clips of eye blinking except for eyelid flutters and microsleeps are extracted from the entire video clip. The changes in shapes and positions of the upper eyelid during the eye blinking sequences are evaluated, and each eye blinking is visualized as a single image. The various parameters regarding eye blinking are calculated to analyze blinking patterns. The single eye blinking sequence is divided into phases to analyze and classify eye blinking patterns in more detail. In this experiment conducted on 80 volunteers, the proposed method was able to quantitatively analyze eyelid movements, and various parameters related to eye blinking were calculated. Additionally, different types of eye blinking patterns were visualized as graph images, and incomplete eye blinking and consecutive eye blinking were defined and detected. The proposed method can overcome the spatial and situational limitations of conventional bio-signal analysis methods, as it allows non-contact measurement in ordinary environments. In addition, since quantitative eye blink data obtained from high-frame-rate video contain more information than data obtained from bio-signals, it is expected that analysis methods using videos can be easily applied to a wider range of fields.