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Fast tuning of observer-based circadian phase estimator using biometric data
Chukwuemeka O Ike1,2, John T Wen1,2, Meeko M K Oishi3
1Lighting Enabled Systems and Applications (LESA) Engineering Research Center, Troy, NY, United States.
Heliyon
|January 13, 2023
Summary
This study introduces a new method for estimating circadian rhythms using a linear state observer. The technique provides continuous, real-time phase estimation from biometric data, improving upon traditional delayed methods.
Area of Science:
- Chronobiology
- Biomedical Engineering
- Signal Processing
Background:
- Circadian rhythms are crucial for well-being, regulated by the suprachiasmatic nuclei (SCN).
- Current circadian phase estimation methods rely on indirect measurements and suffer from significant delays.
- The inaccessibility of the SCN hinders direct assessment of circadian state.
Purpose of the Study:
- To develop a continuous and real-time method for circadian phase estimation.
- To overcome the limitations of delayed and invasive traditional methods.
- To utilize biometric signals for accurate circadian state assessment.
Main Methods:
- Proposed a linear state observer for continuous phase estimation.
- Designed an observer-based filter to isolate frequency components from biometric signals.
- Tuned observer gains using an evolutionary optimization algorithm with a fixed 24-hour oscillatory frequency.
Main Results:
- The developed filter successfully estimated circadian phase from minute-to-minute actigraphy data.
- Achieved an average absolute error within 1.5 hours across all test subjects.
- Demonstrated the feasibility of online circadian phase estimation under ambulatory conditions.
Conclusions:
- The linear state observer offers an elegant and effective solution for continuous circadian phase estimation.
- This approach overcomes the delay issues associated with conventional methods.
- Enables real-time monitoring of circadian state using readily available biometric data.
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