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




Raju, Mehedi H.
Friedman, Lee
Lohr, Dillon J.
Komogortsev, Oleg V.

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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-(≈ 20 min) and long-term (≈ 1 year) biometric evaluations. Understanding the location of identity data within the eye movement spectrum is essential for privacy preservation.



eye movement, biometric, signal, noise


Mehedi Hasan Raju, Lee Friedman, Dillon J. Lohr, and Oleg V. Komogortsev. 2024. Signal vs Noise in Eye-tracking Data: Biometric Implications and Identity Information Across Frequencies. In 2024 Symposium on Eye Tracking Research and Applications (ETRA ’24), June 4–7, 2024, Glasgow, United Kingdom. ACM, New York, NY, USA, 7 pages.


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