Near-sensor computing-assisted simultaneous viral antigen and antibody detection via integrated label-free biosensors with microfluidicsopen access
- Authors
- Bae, Byungjoon; Baek, Yongmin; Yang, Jeongyong; Lee, Heesung; Sonnadara, Charana S. S.; Jung, Sangeun; Park, Minseong; Lee, Doeon; Kim, Sihwan; Giri, Gaurav; Shah, Sahil; Yoo, Geonwook; Petri, William A. A.; Lee, Kyusang
- Issue Date
- Oct-2023
- Publisher
- WILEY
- Keywords
- artificial intelligence; biosensor; edge-computing; integration; microfluidic
- Citation
- INFOMAT, v.5, no.10
- Journal Title
- INFOMAT
- Volume
- 5
- Number
- 10
- URI
- https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/44595
- DOI
- 10.1002/inf2.12471
- ISSN
- 2567-3165
- Abstract
- Precise diagnosis and immunity to viruses, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) is achieved by the detection of the viral antigens and/or corresponding antibodies, respectively. However, a widely used antigen detection methods, such as polymerase chain reaction (PCR), are complex, expensive, and time-consuming Furthermore, the antibody test that detects an asymptomatic infection and immunity is usually performed separately and exhibits relatively low accuracy. To achieve a simplified, rapid, and accurate diagnosis, we have demonstrated an indium gallium zinc oxide (IGZO)-based biosensor field-effect transistor (bio-FET) that can simultaneously detect spike proteins and antibodies with a limit of detection (LOD) of 1 pg mL(-1) and 200 ng mL(-1), respectively using a single assay in less than 20 min by integrating microfluidic channels and artificial neural networks (ANNs). The near-sensor ANN-aided classification provides high diagnosis accuracy (>93%) with significantly reduced processing time (0.62%) and energy consumption (5.64%) compared to the software-based ANN. We believe that the development of rapid and accurate diagnosis system for the viral antigens and antibodies detection will play a crucial role in preventing global viral outbreaks.
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