dc.contributor.advisor | Ahmed, Dr. Tarem | |
dc.contributor.author | Shemonti, Nazifa Mubashshera | |
dc.contributor.author | Chakraborty, Arnoba | |
dc.contributor.author | Ibnat, Aniqa Afra | |
dc.date.accessioned | 2016-09-20T07:47:49Z | |
dc.date.available | 2016-09-20T07:47:49Z | |
dc.date.copyright | 2016 | |
dc.date.issued | 2016-08 | |
dc.identifier.other | ID 12210010 | |
dc.identifier.other | ID 12210014 | |
dc.identifier.other | ID 12210016 | |
dc.identifier.uri | http://hdl.handle.net/10361/6428 | |
dc.description | This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2016. | en_US |
dc.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 11-12). | |
dc.description.abstract | In this paper, a previously developed algorithm based on self implementation and kernel mapping is executed in medical field to develop an automated, ICU signalling. The method is taken into consideration because it is adaptive, portable and has lower complexity in comparison to contemporary approaches. The proposed algorithm takes in set of different medical parameters to monitor the conditions of individual patients in an ICU. Application of real data and the learning mechanism of underlying patterns of the algorithm results in instantaneous detection and alarming in response to critical circumstances. In addition, the system yields recognition's with minimum false alarms. | en_US |
dc.description.statementofresponsibility | Nazifa Mubashshera Shemonti | |
dc.description.statementofresponsibility | Arnoba Chakraborty | |
dc.description.statementofresponsibility | Aniqa Afra Ibnat | |
dc.format.extent | 33 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | KOAD | en_US |
dc.subject | ICU signalling | en_US |
dc.title | KOAD implemented automatic ICU signalling and error minimization | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Electrical and Electronic Engineering, BRAC University | |
dc.description.degree | B. Electrical and Electronic Engineering | |