Yeom, Junyeong Song, Minseop Choi, June Heang Pyeon, You Jang Cho, Jeonghoon Kim, Hyunjoong Cho, Sanghyeon Lee, Yunsik Lee, Yi Jae Kim, Jae Joon 2025-04-22T02:00:12Z 2025-04-22T02:00:12Z 2025-04-21 2025-10 1549-8328 https://pubs.kist.re.kr/handle/201004/152282 An on-chip classifying biochemical multi-sensor integrated interface is presented for diseases diagnosis applications, including diabetes and liver diseases. Against critical problems of sensor drift over time and long settling time from analyte concentration variations, two proposed circuit-level schemes of anti-drift normalization and settling-period detection are designed by utilizing two different detectors of min-max and level-crossing. For disease classification without computation burden in edge-computing devices, an on-chip analog neural network circuit is included together, and the whole readout integrated circuit (ROIC) is fabricated in a 0.18-μm CMOS process. A system-level prototype with an in-house organic electrochemical transistor (OECT) sensor array was implemented and experimentally verified to provide biochemical sensing of four electrolyte ions and glucose. It achieved on-chip classification model F1 scores of 0.79 and 0.72 on diabetes and liver disease respectively. English Institute of Electrical and Electronics Engineers A Chronic Diseases Detection Integrated Interface With Anti-Drift Normalization and On-Chip Classification Schemes Article 10.1109/tcsi.2025.3547720 1 IEEE Transactions on Circuits and Systems I: Regular Papers, v.72, no.10, pp.5482 - 5493 IEEE Transactions on Circuits and Systems I: Regular Papers 72 10 5482 5493 N scie scopus 001470769700001 Engineering, Electrical & Electronic Engineering Article System-on-chip Circuits Calibration Artificial intelligence Accuracy Neural networks Detectors Electrolytes Real-time systems Disease readout integrated circuit anti-drift level-crossing on-chip classification OECT sensor Diseases