| dc.contributor.author | Muhammad Naufal, Mansor | |
| dc.contributor.author | Syahryull Hi-Fi Syam, Ahmad Jamil | |
| dc.contributor.author | Muhammad Nazri, Rejab | |
| dc.contributor.author | Addzrull Hi-Fi Syam, Ahmad Jamil | |
| dc.date.accessioned | 2013-07-10T08:15:17Z | |
| dc.date.available | 2013-07-10T08:15:17Z | |
| dc.date.issued | 2012-08-25 | |
| dc.identifier.citation | p. 374-376 | en_US |
| dc.identifier.isbn | 978-146732467-0 | |
| dc.identifier.uri | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6324598 | |
| dc.identifier.uri | http://dspace.unimap.edu.my/123456789/26565 | |
| dc.description | Link to publisher's homepage at http://ieeexplore.ieee.org | en_US |
| dc.description.abstract | Pain Assessment in Neonatal has been discussed recently nowadays. A rapid research, equipment and pain course has yet been improved. However, the robustness, accurate and fast pain scheme is yet far beyond the schedule comparing to the pain assessment for the adult patient. Thus, an infant pain detection scheme is been proposed based on Autoregressive Model (AR Model) and Fuzzy k-NN. The accuracy result is quite promising around 90.77%. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.relation.ispartofseries | Proceedings of the International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA 2012) | en_US |
| dc.subject | AR Model | en_US |
| dc.subject | Detection of facial changes | en_US |
| dc.subject | Fuzzy k-NN classifier | en_US |
| dc.subject | NICU patient | en_US |
| dc.title | AR model for infant pain anxiety recognition using fuzzy k-NN | en_US |
| dc.type | Working Paper | en_US |
| dc.contributor.url | apairia@yahoo.com | en_US |
| dc.contributor.url | syahrull30@yahoo.com | en_US |
| dc.contributor.url | nazri_554@yahoo.com | en_US |
| dc.contributor.url | azrulhifisyam@yahoo.com | en_US |
