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Optimal bandwidth selection in stochastic regression of Bio-FET measurements
Luis A Melara1, Ryan M Evans2, Seulki Cho3
1Department of Mathematics, Shippensburg University of Pennsylvania, 1871 Old Main Drive, Shippensburg, 17257, PA, USA.
Journal of Mathematical Biology
|June 10, 2025
Summary
This study optimizes noise reduction in biological field effect transistors (Bio-FETs) by determining the best bandwidth parameter for stochastic regression. The findings show consistent optimal parameters across different Bio-FET designs, improving biomarker measurement accuracy.
Area of Science:
- Bioelectronics
- Signal Processing
- Biomedical Engineering
Background:
- Biological field effect transistors (Bio-FETs) provide rapid, cost-effective point-of-care biomarker detection.
- Time-series data from Bio-FETs often contain noise, hindering accurate quantitative analysis.
- Stochastic regression is a method used to denoise Bio-FET measurements by modeling signal drift and diffusion.
Purpose of the Study:
- To determine the optimal bandwidth parameter for stochastic regression in Bio-FET measurements.
- To evaluate the impact of different kernel functions on noise reduction.
- To assess the consistency of optimal bandwidth parameters across various instrument aspect ratios.
Main Methods:
- Stochastic regression modeling using a linear drift-diffusion equation.
- Estimation of coefficients via local weighted regression and maximum likelihood estimation.
- Cross-validation of kernel functions and bandwidth parameters across different Bio-FET aspect ratios.
Main Results:
- Optimal bandwidth parameters were identified for Bio-FET measurements.
- The optimal bandwidth parameters showed remarkable consistency across different instrument aspect ratios.
- The choice of kernel function was found to influence the optimal bandwidth selection.
Conclusions:
- A method for optimizing noise reduction in Bio-FET data has been established.
- Consistent optimal bandwidth parameters simplify the application of stochastic regression for Bio-FET analysis.
- The findings facilitate more accurate and reliable biomarker quantification from Bio-FET devices.
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