Adaptive Circadian Phase Estimation via Real-Time Signal Tracking
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Solution Overview
Problem
Current methods for estimating circadian phase are invasive, time-consuming, and rely on batch-based processing, which limits real-time monitoring and individualized circadian rhythm regulation, especially for applications like cancer treatment and shift work adjustments.
Innovation Solution
A method using adaptive frequency tracking and linear parameter-varying system formulation to estimate circadian phase from biological signals, allowing for real-time, model-free, and personalized circadian rhythm modeling and regulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If batch-based processing methods are used for circadian phase estimation, then measurement precision can be maintained, but processing time and real-time monitoring capability are significantly reduced
Solution Approach 1:
The patent implements dynamic circadian phase estimation by transitioning from static batch processing to continuous real-time monitoring. The system dynamically updates circadian phase estimates as new biological signal data becomes available, enabling adaptive tracking of circadian rhythms without requiring complete data sets before computation. This dynamic approach maintains measurement precision while dramatically reducing processing delays.
Solution Approach 2:
The patent applies preliminary action by pre-computing and storing circadian rhythm models and parameter relationships before actual monitoring begins. These pre-established models enable rapid real-time estimation without requiring complex computations during the monitoring phase, thus maintaining accuracy while minimizing processing time during actual use.
2Measurement precision
If invasive measurement methods are used for circadian phase estimation, then measurement precision is improved, but ease of operation and subject comfort deteriorate
Solution Approach 1:
The patent replaces invasive mechanical or surgical measurement methods with non-invasive optical and physiological sensing techniques. By using light-based circadian rhythm assessment and non-invasive biological signal monitoring (such as melanopic lux measurements and peripheral physiological markers), the system achieves accurate circadian phase estimation without penetrating or disrupting bodily tissues, thereby improving ease of operation and subject comfort.
Solution Approach 2:
The patent introduces intermediary biological markers and physiological signals that can be measured non-invasively but still provide accurate information about circadian phase. These intermediaries (such as peripheral temperature rhythms, hormone secretion patterns, or behavioral markers) serve as mediators between the central circadian pacemaker and external measurement devices, enabling indirect but accurate assessment without direct invasion of the circadian control centers.
3Device complexity
If generic circadian rhythm models are used, then device complexity is reduced, but adaptability to individual subjects deteriorates
Solution Approach 1:
The patent implements dynamic model adaptation where generic circadian rhythm models serve as initial templates that automatically adjust to individual subject characteristics. The system dynamically updates model parameters based on each subject's specific biological responses, light exposure patterns, and physiological data, enabling personalized circadian rhythm regulation while maintaining computational efficiency through the use of adaptable rather than fully custom models.
Solution Approach 2:
The patent applies parameter changes by modifying key model parameters (such as free-running period, phase response curves, and entrainment sensitivity) based on individual subject data. Rather than changing the fundamental model structure, the system adjusts specific parameters to reflect individual variations in circadian biology, achieving personalized regulation with minimal increase in device complexity.
Data Source
AI summary
Method, system and computer program product are provided for estimating a circadian phase of a subject by: obtaining a sensed biological signal for the subject; and using, by one or more processors, adaptive frequency tracking to adaptively estimate the circadian phase of the subject from the sensed biological signal. Circadian phase estimation may be accelerated by providing a feedback loop for the adaptive frequency tracking, which utilizes, in part, a circadian phase model in automatically ascertaining a phase correction for the adaptive frequency tracking. The circadian phase estimation may be used in automatically constructing a light-based circadian rhythm model for the subject using a linear parameter-varying (LPV) formulation, and once constructed, the circadian rhythm model for the subject may be used to provide light-based circadian rhythm regulation.