Ike CO, Wen JT, Oishi MMK, Brown LK, Julius AA. Efficient Estimation of the Human Circadian Phase via Kalman Filtering.
ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;
2023:1-6. [PMID:
38083233 DOI:
10.1109/embc40787.2023.10340241]
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Abstract
Circadian rhythms play a vital role in maintaining a person's well-being but remain difficult to quantify accurately. Numerous approaches exist to measure these rhythms, but they often suffer from performance issues on the individual level. This work implements a Steady-State Kalman Filter as a method for estimating the circadian phase shifts from biometric signals. Our framework can automatically fit the filter's parameters to biometric data obtained for each individual, and we were able to consistently estimate the phase shift within 1 hour of melatonin estimates on 100% of all subjects in this study. The estimation method opens up the possibility of real-time control and assessment of the circadian system, as well as chronotherapeutic intervention.Clinical relevance- This establishes a near real-time alternative to melatonin measurements for the estimation of circadian phase shifts, with potential applications in feedback circadian control and chronotherapeutics.
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