Optical Measurement Device Dynamic IRF Calibration
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Solution Overview
Problem
Optical measurement devices face challenges in accurately determining blood oxygenation and neural activity due to changes in instrument response functions (IRFs) caused by varying device properties such as temperature and current, which affect the calibration of laser pulse shapes.
Innovation Solution
The device dynamically determines the IRF while in use by analyzing histogram data and adjusting for changes in device properties, using methods like lookup tables and machine learning algorithms to maintain accurate calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed baseline shape (IRF) is used for calibration, then device structure is simple, but measurement precision deteriorates due to IRF changes from temperature and current variations
Solution Approach 1:
The patent implements dynamic IRF determination by continuously monitoring device properties (temperature, current) and updating the baseline shape accordingly. The processing unit dynamically adjusts the IRF based on real-time device property changes, transforming the static calibration approach into a dynamic one that adapts to environmental variations, thereby maintaining measurement precision without requiring overly complex hardware modifications
Solution Approach 2:
The system establishes a feedback loop where device properties (temperature, current) are continuously monitored and fed back to the processing unit. This feedback mechanism enables the system to automatically adjust the IRF based on detected changes in device properties, ensuring that the baseline shape remains accurate despite environmental variations. The feedback loop closes the gap between fixed calibration and actual operating conditions
2Reliability
If dynamic IRF determination is implemented, then measurement precision is maintained, but device complexity and processing requirements increase
Solution Approach 1:
The patent implements preliminary characterization of the device properties and their relationship to IRF changes. Lookup tables and pre-computed correction factors are stored in memory, allowing the processing unit to quickly retrieve and apply appropriate IRF adjustments without performing complex real-time calculations. This preliminary preparation reduces the computational burden during actual measurement operations while maintaining reliability
Solution Approach 2:
The system creates and stores multiple copies of IRF data corresponding to different device property states in a lookup table. Instead of computing new IRF values during operation, the processing unit simply retrieves the appropriate pre-computed IRF copy based on current device properties. This copying approach significantly reduces processing complexity while maintaining measurement reliability
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for more precise determination of blood oxygenation and neural activity by compensating for IRF variations, ensuring accurate measurements despite environmental and operational changes.
Implementation Method 1
a detector configured to detect arrival times for photons of the light pulses after the photons are scattered by the target
Data Source
AI summary
An illustrative optical measurement device includes a light source configured to emit light pulses directed at a target of a user. The optical measurement device further includes a detector configured to detect arrival times for photons of the light pulses after the photons are scattered by the target. The optical measurement device further includes a processing unit configured to determine, while the optical measurement device is being worn by the user, an instrument response function (IRF) associated with the optical measurement device. The processing unit is further configured to generate, based on the arrival times of the photons at the detector, histogram data associated with the target. The processing unit is further configured to determine, based on the IRF and the histogram data, a property of the target.