# Non-contact, real-time eye blink detection with capacitive sensing

arXiv: https://arxiv.org/abs/2211.05541 · HTML: https://mlsanity.com/paper/2211.05541/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Nov 2022.

## Built on by (most cited first, 4 of 4)

- [TinierHAR: Towards Ultra-Lightweight Deep Learning Models for Efficient Human Activity Recognition on Edge Devices](https://mlsanity.com/paper/2507.07949/) (2025)
- [PupilSense: A Novel Application for Webcam-Based Pupil Diameter Estimation](https://mlsanity.com/paper/2407.11204/) (2024)
- [Webcam-based Pupil Diameter Prediction Benefits from Upscaling](https://mlsanity.com/paper/2408.10397/) (2024)
- [Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Survey](https://mlsanity.com/paper/2401.06000/) (2024)

## Abstract (arXiv)

This work described a novel non-contact, wearable, real-time eye blink detection solution based on capacitive sensing technology. A low-cost and low-power consumption capacitive sensing prototype was developed and deployed on a pair of standard glasses with a copper electrode attached to the glass frame. The eye blink action will cause the capacitance variation between the electrode and the eyelid. Thus by monitoring the capacitance variation caused oscillating frequency shift signal, the eye blink can be abstracted by a simple comparison of the raw frequency signal with a customized threshold. The feasibility and robustness of the proposed solution were demonstrated in five scenarios performed by eight volunteers with an average precision of 92% and recall of 94%.