Biosensor Digital Filter and Selective Window for Noise Reduction
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Solution Overview
Problem
Biosensors, particularly pH sensors, face challenges with long settling times and noise in output signals due to chemical flow, bio-reactions, and detection methods, which affect their performance and accuracy.
Innovation Solution
A biosensor system incorporating a digital filter and selective window to enhance signal-to-noise resolution (SNR) is introduced, along with a feedback network and tuning circuit for self-calibration, allowing for improved signal processing and adjustment of biosensor sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional pH sensor detection methods are used, then the sensor can detect biological conditions, but the output signal contains significant noise and requires long settling times
Solution Approach 1:
The patent segments the digital signal into multiple bits representing different time windows, allowing selective processing of signal portions. By dividing the signal into discrete bit segments that can be individually filtered and weighted, the system achieves noise reduction without requiring long overall settling times, as each segment can be processed independently and quickly.
Solution Approach 2:
The patent implements periodic sampling and filtering of the biosensor output signal, using repeated measurements at different time points to build up a statistically significant signal. This periodic action allows the system to achieve high signal-to-noise ratios through averaging multiple rapid measurements rather than requiring a single long settling period.
2Measurement precision
If traditional signal processing methods are used, then the biosensor output can be read, but noise from chemical flow and bio-reactions degrades accuracy
Solution Approach 1:
The patent applies preliminary digital filtering and signal processing to the raw biosensor output before final measurement. By pre-processing the signal to identify and weight stable bit portions while suppressing noisy portions, the system eliminates noise effects before they can degrade the final measurement accuracy.
Solution Approach 2:
The patent creates multiple digital representations (copies) of the biosensor signal at different time points and processing stages. By generating multiple bit copies that can be compared, filtered, and averaged, the system identifies and eliminates noise through redundancy, keeping only the consistent signal portions that represent true biological conditions.
3Measurement precision
If biosensor sensitivity is increased to improve detection, then the sensor responds more strongly to biological conditions, but the sensor becomes more susceptible to noise and requires recalibration
Solution Approach 1:
The patent implements feedback mechanisms where the processed signal information is used to adjust and optimize the biosensor operating parameters. By continuously monitoring the signal quality and adjusting sensitivity parameters based on measured performance, the system maintains high sensitivity while compensating for noise susceptibility through active control and recalibration.
Data Source
AI summary
A device includes a biosensor, a sensing circuit electrically connected to the biosensor, a quantizer electrically connected to the sensing circuit, a digital filter electrically connected to the quantizer, a selective window electrically connected to the digital filter, and a decision unit electrically connected to the selective window.