Automating hospital ICU emergency signaling

dc.contributor.author	Zahan, Fahmida
dc.contributor.author	Mahmud, Nusrat
dc.contributor.author	Nawshin, Amanna
dc.contributor.author	Ahmed, Ferdousi
dc.date.accessioned	2015-07-02T07:43:53Z
dc.date.available	2015-07-02T07:43:53Z
dc.date.issued	2015-04
dc.identifier.other	ID 10301012
dc.identifier.other	ID 10301015
dc.identifier.other	ID 10310003
dc.identifier.other	ID 10310010
dc.identifier.uri	http://hdl.handle.net/10361/4211
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, 2015.	en_US
dc.description.abstract	This thesis verifies that the proposed Kernel mapping based recursive least square algorithm can detect the slightest deviation of anomaly from the norm, monitor and learn underlying pattern between natural and abnormal multivariate medical parameters of a particular critical ICU patient with high detection accuracy and very low rate of false alarm. This online, automated, sequential, real-time intruder detection algorithm is suitable for any instantaneous detection of accidental emergencies without compromising the patient safety and effectiveness of care. It is an elegant, inexpensive solution, independent of complexity, and also a portable and adaptive approach.	en_US
dc.language.iso	en	en_US
dc.publisher	BRAC University	en_US
dc.subject	Electrical and electronic engineering	en_US
dc.title	Automating hospital ICU emergency signaling	en_US
dc.type	Thesis	en_US