DocumentCode :
262479
Title :
24.5 A 0.5V 1.27mW nose-on-a-chip for rapid diagnosis of ventilator-associated pneumonia
Author :
Kea-Tiong Tang ; Shih-Wen Chiu ; Chung-Hung Shih ; Chia-Ling Chang ; Chia-Min Yang ; Da-Jeng Yao ; Jen-Huo Wang ; Chien-Ming Huang ; Hsin Chen ; Kwuang-Han Chang ; Chih-Cheng Hsieh ; Ting-Hau Chang ; Meng-Fan Chang ; Chia-Min Wang ; Yi-Wen Liu ; Tsan-Jieh
Author_Institution :
Nat. Tsing Hua Univ., Hsinchu, Taiwan
fYear :
2014
fDate :
9-13 Feb. 2014
Firstpage :
420
Lastpage :
421
Abstract :
Ventilator-associated pneumonia (VAP) is the most frequently acquired infection among patients that receive mechanical ventilation in the intensive-care unit (ICU). The mortality rate for VAP lies in the 20-to-50% range and could be even higher in some ICUs. A standard operation procedure to VAP treatment includes a sequence of chest radiography, sputum gram stain, sputum culture, and empiric therapy, initially with antibiotics covering broad pathogens. However, collection of the gram stain and culture of lower respiratory tract specimen is usually not time-efficient (up to 5 days), delaying the initiation of therapy and unacceptable for critically ill patients. A rapid and accurate diagnosis for VAP is therefore crucial, but still unavailable. It is known that microorganisms generate complex metabolites during infection. Fast detection is feasible by examining metabolic wastes in proximal end of the expiratory device, demanding a miniaturized, battery-powered, gas-sensing device. In this work, a fully integrated low-power nose-on-a-chip with a robust learning kernel is developed for such a vital clinical need.
Keywords :
biomedical electronics; diagnostic radiography; diseases; drug delivery systems; drugs; gas sensors; health care; low-power electronics; microorganisms; patient care; patient diagnosis; ventilation; antibiotics; chest radiography; complex metabolites; critically ill patients; empiric therapy; expiratory device; frequently acquired infection; fully integrated low-power nose-on-a-chip; intensive-care unit; lower respiratory tract specimen; mechanical ventilation; metabolic wastes; microorganisms; miniaturized battery-powered gas-sensing; mortality rate; pathogens; power 1.27 mW; rapid diagnosis; robust learning kernel; sputum culture; sputum gram stain; therapy; ventilator-associated pneumonia treatment; voltage 0.5 V; Accuracy; Kernel; Mesoporous materials; Reduced instruction set computing; Robustness; Sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Solid-State Circuits Conference Digest of Technical Papers (ISSCC), 2014 IEEE International
Conference_Location :
San Francisco, CA
ISSN :
0193-6530
Print_ISBN :
978-1-4799-0918-6
Type :
conf
DOI :
10.1109/ISSCC.2014.6757496
Filename :
6757496
Link To Document :
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