A Fully Integrated Nose-on-a-Chip for Rapid Diagnosis of Ventilator-Associated Pneumonia

IEEE transactions on biomedical circuits and systems(2015)

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摘要
Ventilator-associated pneumonia (VAP) still lacks a rapid diagnostic strategy. This study proposes installing a nose-on-a-chip at the proximal end of an expiratory circuit of a ventilator to monitor and to detect metabolite of pneumonia in the early stage. The nose-on-a-chip was designed and fabricated in a 90-nm 1P9M CMOS technology in order to downsize the gas detection system. The chip has eight on-chip sensors, an adaptive interface, a successive approximation analog-to-digital converter (SAR ADC), a learning kernel of continuous restricted Boltzmann machine (CRBM), and a RISC-core with low-voltage SRAM. The functionality of VAP identification was verified using clinical data. In total, 76 samples infected with pneumonia (19 Klebsiella, 25 Pseudomonas aeruginosa, 16 Staphylococcus aureus, and 16 Candida) and 41 uninfected samples were collected as the experimental group and the control group, respectively. The results revealed a very high VAP identification rate at 94.06% for identifying healthy and infected patients. A 100% accuracy to identify the microorganisms of Klebsiella, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida from VAP infected patients was achieved. This chip only consumes 1.27 mW at a 0.5 V supply voltage. This work provides a promising solution for the long-term unresolved rapid VAP diagnostic problem.
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关键词
ventilator-associated pneumonia,clinical data,successive approximation analog-to-digital converter,RISC-core,long-term unresolved rapid VAP diagnostic problem,gas detection system,VAP identification functionality,CMOS integrated circuits,nose-on-a-chip,Candida,Boltzmann machines,diseases,fully integrated nose-on-a-chip,analogue-digital conversion,expiratory circuit,power 1.27 mW,voltage 0.5 V,metabolite detection,microorganisms,Continuous restricted Boltzmann machine (CRBM),low-voltage SRAM,patient monitoring,low-power electronics,adaptive interface,learning kernel,rapid diagnostic strategy,1P9M CMOS technology,ventilator-associated pneumonia (VAP),metabolite monitoring,VAP identification rate,SAR ADC,CRBM,lab-on-a-chip,Klebsiella,on-chip sensors,Staphylococcus aureus,electronic noses,medical diagnostic computing,continuous restricted Boltzmann machine,patient diagnosis,Pseudomonas aeruginosa,gas classification
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