Continuous Circadian Phase Estimation Using Adaptive Notch Filter

TL;DR

This paper introduces an adaptive notch filter method for real-time circadian phase estimation from actigraphy data, demonstrated on fruit fly datasets, offering a potentially more efficient alternative to traditional regression approaches.

Contribution

The paper proposes a novel adaptive filtering technique for online circadian phase estimation, improving real-time analysis of biometric data.

Findings

Effective phase estimation on fruit fly data

Potential for real-time circadian monitoring

Improved over traditional regression methods

Abstract

Actigraphy has been widely used for the analysis of circadian rhythm. Current practice applies regression analysis to data from multiple days to estimate the circadian phase. This paper presents a filtering method for online processing of biometric data to estimate the circadian phase. We apply the proposed method on actigraphy data of fruit flies (Drosophila melanogaster).