Tracking Blink Dynamics and Mental States on Glasses

Eye blink dynamics offer crucial insights into physiological and cognitive states. Existing solutions either require specialized equipment for detailed measurements or sacrifice temporal resolution for accessibility. We present BlinkWise, the first system that transforms everyday eyewear into a wise device for detailed blink dynamics tracking as a tiny add-on. BlinkWise measures eye openness in real-time on resource-constrained edge devices by leveraging both RF modality's inherent efficiency and novel computational optimizations—including recurrentization of convolutional network operations, quantization-aware normalization, and a lightweight proposal algorithm. Evaluation with 20 subjects and more than 18,000 blink measurements demonstrated BlinkWise's high accuracy in capturing subtle blink dynamics at millisecond resolution, achieving a Pearson correlation of 0.981 with ground truth. Through three real-world application studies, we demonstrate BlinkWise's potential for monitoring cognitive states and ocular health. Code, datasets, and demo videos are available on our website.

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Published
2025-06-23
DOI
https://doi.org/10.1145/3711875.3729150
Primary Topic
Visual perception and processing mechanisms
Type
article
Field-Weighted Citation Impact
0.00

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article

Tracking Blink Dynamics and Mental States on Glasses

M. Zhao, Insup Lee, Xin Yang, Ahhyun Yuh et al.
Visual perception and processing mechanisms
article

Tracking Blink Dynamics and Mental States on Glasses

M. Zhao, Insup Lee, Xin Yang, Ahhyun Yuh, Dongyin Hu, Z. Y. Wang, Lama A. Al‐Aswad
article en

Abstract

Eye blink dynamics offer crucial insights into physiological and cognitive states. Existing solutions either require specialized equipment for detailed measurements or sacrifice temporal resolution for accessibility. We present BlinkWise, the first system that transforms everyday eyewear into a wise device for detailed blink dynamics tracking as a tiny add-on. BlinkWise measures eye openness in real-time on resource-constrained edge devices by leveraging both RF modality's inherent efficiency and novel computational optimizations—including recurrentization of convolutional network operations, quantization-aware normalization, and a lightweight proposal algorithm. Evaluation with 20 subjects and more than 18,000 blink measurements demonstrated BlinkWise's high accuracy in capturing subtle blink dynamics at millisecond resolution, achieving a Pearson correlation of 0.981 with ground truth. Through three real-world application studies, we demonstrate BlinkWise's potential for monitoring cognitive states and ocular health. Code, datasets, and demo videos are available on our website.

University of Pennsylvania (US), Philadelphia University (US)
University of Pennsylvania
Openalex Percentile: Top 73%
Visual perception and processing mechanisms
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Tracking Blink Dynamics and Mental States on Glasses — M. Zhao, Insup Lee, et al. · (2025) | TGRS Research Map | TGRS