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dc.contributor.authorChou, Ting-Ien_US
dc.contributor.authorChiu, Shih-Wenen_US
dc.contributor.authorChang, Kwuang-Hanen_US
dc.contributor.authorChen, Yi-Juen_US
dc.contributor.authorTang, Chen-Tingen_US
dc.contributor.authorShih, Chung-Hungen_US
dc.contributor.authorHsieh, Chih-Chengen_US
dc.contributor.authorChang, Meng-Fanen_US
dc.contributor.authorYang, Chia-Hsiangen_US
dc.contributor.authorChiueh, Hermingen_US
dc.contributor.authorTang, Kea-Tiongen_US
dc.date.accessioned2018-08-21T05:56:44Z-
dc.date.available2018-08-21T05:56:44Z-
dc.date.issued2016-01-01en_US
dc.identifier.issn2163-4025en_US
dc.identifier.urihttp://hdl.handle.net/11536/146568-
dc.description.abstractChronic obstructive pulmonary disease (COPD) still lacks a rapid diagnosis strategy. In this paper, we propose a low-power nose-on-a-chip for rapid COPD screening. This chip is designed for implementation in a personal handheld device that detects patient breath for COPD diagnosis. The chip has 36 on-chip sensors, a 36-channel adaptive interface with an integrated programmable amplifier, a four-channel frequency readout interface, one on-chip temperature sensor, a two-channel successive approximation analog-to-digital converter, a scalable learning kernel cluster, and a reduced instruction set computing core with low-voltage static random-access memory. This chip is fabricated in 90 nm CMOS and consumes 1.68 mW at 0.5 V. In simulation, the system distinguished between undiseased and diseased patients with 90.82% accuracy for a set of diseases including COPD and asthma and exhibited 92.31% accuracy for identifying patients with COPD or asthma. The system classified severity levels of COPD under four labels (normal, mild, moderate, and severe) with 92.00% accuracy. Accordingly, this work provides a promising solution for the unmet medical need of rapid COPD screening.en_US
dc.language.isoen_USen_US
dc.subjectCOPDen_US
dc.subjectNose-on-a-chip systemen_US
dc.subjectSoCen_US
dc.titleDesign of a 0.5V 1.68mW Nose-on-a-Chip for Rapid Screen of Chronic Obstructive Pulmonary Diseaseen_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS OF 2016 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS)en_US
dc.citation.spage592en_US
dc.citation.epage595en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000401795900155en_US
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