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Related Concept Videos

Photoluminescence: Applications01:14

Photoluminescence: Applications

970
Photoluminescence offers a wide range of applications due to its inherent sensitivity and selectivity. This technique allows for both direct and indirect analyses of the analyte. Direct quantitative analysis is possible when the analyte exhibits a favorable quantum yield for fluorescence or phosphorescence. However, an indirect analysis may be feasible if the analyte is not fluorescent or phosphorescent, or if the quantum yield is unfavorable. Indirect methods include reacting the analyte with...
970

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Luminescence Lifetime Imaging of O2 with a Frequency-Domain-Based Camera System
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Comparing Numerical Optimization Algorithms for On-Device Luminescence Lifetime Analysis.

Gokalp Cevik, Vladimir Vakhter, Ulkuhan Guler

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    Summary
    This summary is machine-generated.

    This study compares nonlinear optimization algorithms for on-device luminescence lifetime computation in wearable sensors. Levenberg-Marquardt and BFGS offer reliable convergence, while gradient descent is fastest for oxygen monitoring.

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    Area of Science:

    • Biomedical Engineering
    • Optical Sensing
    • Algorithm Optimization

    Background:

    • Luminescence sensing is vital for biomedical applications like transcutaneous oxygen monitoring and tumor hypoxia detection.
    • Lifetime-based luminescence measurements offer superior reliability over intensity-based methods.
    • Computing luminescence lifetime involves solving nonlinear optimization problems, challenging for low-power wearables.

    Purpose of the Study:

    • To systematically compare nonlinear optimization algorithms for on-device computation of luminescence lifetime.
    • To evaluate algorithm performance based on energy usage, computation time, convergence reliability, and error.
    • To identify optimal algorithms for resource-constrained wearable platforms.

    Main Methods:

    • Comparison of Gauss-Newton, gradient descent variants, Levenberg-Marquardt, and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithms.
    • Implementation and evaluation on an STM32WB35 microcontroller-based transcutaneous oxygen sensing board.
    • Assessment of energy consumption, processing time, convergence success rate, and measurement error.

    Main Results:

    • Fixed step size gradient descent with optimal parameters demonstrated the fastest execution time.
    • Levenberg-Marquardt and BFGS algorithms exhibited superior convergence reliability and lower error.
    • These advanced algorithms achieved reliable results with moderate computational cost.

    Conclusions:

    • Algorithm selection for on-device luminescence lifetime computation requires balancing speed, reliability, and resource constraints.
    • Levenberg-Marquardt and BFGS are recommended for robust measurements in wearable biomedical devices.
    • Gradient descent offers a faster alternative when computational resources are extremely limited and initial parameters are optimized.