Fault Detection and Identification of COSMED K4b2 based on PCA and Neural Network

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dc.contributor.author Zhou, Jing en_US
dc.contributor.author Su, Steven en_US
dc.contributor.author Guo, Aihuang en_US
dc.contributor.editor Alexander Vaninsky, Arkady Bolotin en_US
dc.date.accessioned 2013-06-28T02:16:57Z
dc.date.available 2013-06-28T02:16:57Z
dc.date.issued 2012 en_US
dc.identifier 2012000303 en_US
dc.identifier.citation Guo, Aihuang, Zhou, Jing, and Su, Steven 2012, 'Fault Detection and Identification of COSMED K4b2 based on PCA and Neural Network', WASET, Penang,Malaysia, pp. 729-734. en_US
dc.identifier.issn 2010-376X en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/23203
dc.description.abstract COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network. en_US
dc.language en_US
dc.publisher WASET en_US
dc.relation.isbasedon en_US
dc.title Fault Detection and Identification of COSMED K4b2 based on PCA and Neural Network en_US
dc.parent WASET:International conference on Information, communication and Signal Processing en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Penang,Malaysia en_US
dc.identifier.startpage 729 en_US
dc.identifier.endpage 734 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 111711 en_US
dc.personcode 11313246 en_US
dc.personcode 997723 en_US
dc.personcode 0000087049 en_US
dc.percentage 30 en_US
dc.classification.name Health Information Systems (incl. Surveillance) en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom International conference on Information, communication and Signal Processing en_US
dc.date.activity 20121206 en_US
dc.location.activity Penang,Malaysia en_US
dc.description.keywords BP Neural Network, Exercising Testing, Fault Detection and Identification, Principal Component Analysis. en_US


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