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Signal processing and machine learning for blood pressure classification using only the ECG signal / (Record no. 75885)

MARC details
000 -LEADER
fixed length control field 02355cam a2200325 a 4500
003 - CONTROL NUMBER IDENTIFIER
control field EG-GiCUC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250223032500.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 191215s2019 ua dh f m 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency EG-GiCUC
Language of cataloging eng
Transcribing agency EG-GiCUC
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title eng
049 ## - LOCAL HOLDINGS (OCLC)
Holding library Deposite
097 ## - Thesis Degree
Thesis Level Ph.D
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number Cai01.13.03.Ph.D.2019.Ab.S
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Abdelrahman Shaaban Sayed Hassan
245 10 - TITLE STATEMENT
Title Signal processing and machine learning for blood pressure classification using only the ECG signal /
Statement of responsibility, etc. Abdelrahman Shaaban Sayed Hassan ; Supervised Amr Abdelrahman Sharawi
246 15 - VARYING FORM OF TITLE
Title proper/short title معالجة الإشارة وتعلم الآلة لتصنيف ضغط الدم باستخدام إشارة رسم القلب فقط
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cairo :
Name of publisher, distributor, etc. Abdelrahman Shaaban Sayed Hassan ,
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Extent 90 P. :
Other physical details charts , facsimiles ;
Dimensions 30cm
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering
520 ## - SUMMARY, ETC.
Summary, etc. Continuous reading of vital signs in the Intensive Care Unit is a major role for the physician, which allows him to intervene in a timely manner. Thus, continuous blood pressure measurement remains a difficult task as long as it is based on using a mercury device or other wide varieties of methods. The approach of this research is based on classifying blood pressure records obtained from the analysis of the Electrocardiogram (ECG) solely using signal processing techniques. The analysis starts with Butterworth filtration of the ECG signal. Following that trend removal and normalization of the signal takes place before extracting 27 features. Feature selection methods are applied to reduce the number of features to the most dominant ones, and as a result the number of features was reduced to 10. The final results point to a high accuracy of 98.18% using a support vector machine (SVM) classifier. Other classifiers like artificial neural networks (ANN) and Bayesian naïve (BN) classifiers were also used but gave a less accuracy of 96.5% and 96.08%, respectively
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Issued also as CD
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Blood pressure
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Electrocardiogram
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term SVM classifier
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Amr Abdelrahman Sharawi ,
Relator term
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://172.23.153.220/th.pdf">http://172.23.153.220/th.pdf</a>
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Asmaa
Reviser Cataloger
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Nazla
Reviser Revisor
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
Holdings
Source of classification or shelving scheme Not for loan Home library Current library Date acquired Full call number Barcode Date last seen Koha item type Copy number
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة قاعة الرسائل الجامعية - الدور الاول 11.02.2024 Cai01.13.03.Ph.D.2019.Ab.S 01010110080349000 22.09.2023 Thesis  
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة مخـــزن الرســائل الجـــامعية - البدروم 11.02.2024 Cai01.13.03.Ph.D.2019.Ab.S 01020110080349000 22.09.2023 CD - Rom 80349.CD