# Signal vs Noise in Eye-tracking Data: Biometric Implications and Identity Information Across Frequencies

arXiv: https://arxiv.org/abs/2305.04413 · HTML: https://mlsanity.com/paper/2305.04413/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 May 2023.

## Built on by (most cited first, 3 of 3)

- [Temporal Persistence and Intercorrelation of Embeddings Learned by an End-to-End Deep Learning Eye Movement-driven Biometrics Pipeline](https://mlsanity.com/paper/2402.16399/) (2024)
- [Ocular Authentication: Fusion of Gaze and Periocular Modalities](https://mlsanity.com/paper/2505.17343/) (2025)
- [Gaze Authentication: Factors Influencing Authentication Performance](https://mlsanity.com/paper/2509.10969/) (2025)

## Abstract (arXiv)

Prior research states that frequencies below 75 Hz in eye-tracking data represent the primary eye movement termed ``signal'' while those above 75 Hz are deemed ``noise''. This study examines the biometric significance of this signal-noise distinction and its privacy implications. There are important individual differences in a person's eye movement, which lead to reliable biometric performance in the ``signal'' part. Despite minimal eye-movement information in the ``noise'' recordings, there might be significant individual differences. Our results confirm the ``signal'' predominantly contains identity-specific information, yet the ``noise'' also possesses unexpected identity-specific data. This consistency holds for both short-(approx. 20 min) and long-term (approx. 1 year) biometric evaluations. Understanding the location of identity data within the eye movement spectrum is essential for privacy preservation.