Stable EEG Source Estimation for Standardized Kalman Filter using Change Rate Tracking

Joonas Lahtinen

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arXiv · 2504.01984

Stable EEG Source Estimation for Standardized Kalman Filter using Change Rate Tracking

Joonas Lahtinen

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Abstract

This article focuses on the measurement and evolution modeling of Standardized Kalman filtering for brain activity estimation using non-invasive electroencephalography data. Here, we propose new parameter tuning and a model that uses the rate of change in the brain activity distribution to improve the stability of otherwise accurate estimates. Namely, we propose a backward-differentiation-based measurement model for the change rate, which notably improves the filtering-parametrization-stability of the tracking. Simulated data and data from a real subject were used in experiments.

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BibTeX RIS

Joonas Lahtinen. 2025-03-29. Stable EEG Source Estimation for Standardized Kalman Filter using Change Rate Tracking. https://arxiv.org/abs/2504.01984

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