ISFET Array In-Pixel Computation for Classification of Nucleic Acid Amplification

Nucleic acid amplification is a crucial method in infectious disease diagnostic and identification of cancer mutations that allows for informed treatment. The CMOS-fabricated Ion-Sensitive Field-Effect Transistor (ISFET) can be exploited at the Point-of-Care as part of a handheld Lab-on-Chip (LoC) device thanks to its pH sensitivity to achieve real-time sensing of the hydrogen release during amplification. Current approaches involve off-chip processing of the sensor data, introducing challenges due to the amount of data to be transmitted and analysed, and to ensure patient privacy in a procedure that involves multiple data transfers. This paper proposes a pixel architecture for real-time in-pixel classification of the sensor data. A 4x4 ISFET array is shown, with a design that allows for full scalability to a much larger device. The system is developed in TSMC 65nm technology, resulting in a total pixel area of 51.4x49.54μm. Classification of positive and negative experiments is simulated with ideal and real experimental data.

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Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11044279
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
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article

ISFET Array In-Pixel Computation for Classification of Nucleic Acid Amplification

Nicolas Moser, Pantelis Georgiou, Costanza Gulli
Advanced biosensing and bioanalysis techniques
article

ISFET Array In-Pixel Computation for Classification of Nucleic Acid Amplification

Nicolas Moser, Pantelis Georgiou, Costanza Gulli
article en

Abstract

Nucleic acid amplification is a crucial method in infectious disease diagnostic and identification of cancer mutations that allows for informed treatment. The CMOS-fabricated Ion-Sensitive Field-Effect Transistor (ISFET) can be exploited at the Point-of-Care as part of a handheld Lab-on-Chip (LoC) device thanks to its pH sensitivity to achieve real-time sensing of the hydrogen release during amplification. Current approaches involve off-chip processing of the sensor data, introducing challenges due to the amount of data to be transmitted and analysed, and to ensure patient privacy in a procedure that involves multiple data transfers. This paper proposes a pixel architecture for real-time in-pixel classification of the sensor data. A 4x4 ISFET array is shown, with a design that allows for full scalability to a much larger device. The system is developed in TSMC 65nm technology, resulting in a total pixel area of 51.4x49.54μm. Classification of positive and negative experiments is simulated with ideal and real experimental data.

Imperial College London (GB)
Openalex Percentile: Top 86%
Advanced biosensing and bioanalysis techniques
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ISFET Array In-Pixel Computation for Classification of Nucleic Acid Amplification — Nicolas Moser, Pantelis Georgiou, et al. · (2025) | TGRS Research Map | TGRS