Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/12099
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMuhammad Naufal, Mansor-
dc.contributor.authorSazali, Yaacob, Prof. Dr.-
dc.contributor.authorNagarajan, Ramachandran, Prof. Dr.-
dc.date.accessioned2011-05-26T01:59:21Z-
dc.date.available2011-05-26T01:59:21Z-
dc.date.issued2011-03-
dc.identifier.citationInternational of Research and Reviews in Artificial Intelligence, vol. 1(1), 2011, pages 20-24en_US
dc.identifier.issn2046-5122-
dc.identifier.urihttp://sciacademypublisher.com/journals/index.php/IJRRAI/article/view/49/42-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/12099-
dc.descriptionLink to publisher's homepage at http://sciacademypublisher.com/en_US
dc.description.abstractReckoning patient grimacing in Intensive Care Unit (ICU) is a crucial demand in checking routine procedure. Despite of detecting any physical change in the body of the patient, medical staff has to go up and down to the patient bed several times and to report to surgeons accurately. By viewing the patient grimacing changes, the surgeons can get full details of the way of changes in physical body; certainly this cannot be explained accurately by the nurses. As such, this series of research is focus on real-time measurement of high resolution facial changes that are observed to occur in agitation. An algorithm is developed that measures the degree of facial grimacing from a single digital camera. The method is demonstrated on simulated patient facial motion to prove the concept. A consistent measure is obtained that is robust to significant random angle head movement and compares well against visual observation of different levels of grimacing. The method provides a basis for clinical validation. Finally, the conditions of the patient were determined based on classifiers such as K-Nearest Neighborhood (k-NN), Fuzzy k-NN (f-kNN), Linear Discriminant Analysis (LDA) and Neural Network (NN).en_US
dc.language.isoenen_US
dc.publisherScience Academy Publisheren_US
dc.subjectFacial grimacingen_US
dc.subjectPatient agitationen_US
dc.subjectIntensive care uniten_US
dc.subjectK-Nearest Neighborhood (k-NN)en_US
dc.subjectFuzzy k-NN (f-kNN)en_US
dc.subjectLinear Discriminant Analysis (LDA)en_US
dc.subjectNeural Network (NN)en_US
dc.titleReckoning of facial grimacing scheme for patient agitation in critical careen_US
dc.typeArticleen_US
dc.contributor.urlapairia@yahoo.comen_US
dc.contributor.urlsazali22@yahoo.comen_US
dc.contributor.urlnagarajan@unimap.edu.myen_US
Appears in Collections:School of Mechatronic Engineering (Articles)
Sazali Yaacob, Prof. Dr.
Ramachandran, Nagarajan, Prof. Dr.

Files in This Item:
File Description SizeFormat 
47-181-1-PB.pdf376.71 kBAdobe PDFView/Open


Items in UniMAP Library Digital Repository are protected by copyright, with all rights reserved, unless otherwise indicated.