NDLI: Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

Content Provider	Springer Nature : BioMed Central
Author	Krupa, Niranjana MA, Mohd Ali Zahedi, Edmond Ahmed, Shuhaila Hassan, Fauziah M
Abstract	Background Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'. Methods The FHR were recorded from 15 subjects at a sampling rate of 4 Hz and a dataset consisting of 90 randomly selected records of 20 minutes duration was formed from these. All records were labelled as 'normal' or 'at risk' by two experienced obstetricians. A training set was formed by 60 records, the remaining 30 left as the testing set. The standard deviations of the EMD components are input as features to a support vector machine (SVM) to classify FHR samples. Results For the training set, a five-fold cross validation test resulted in an accuracy of 86% whereas the overall geometric mean of sensitivity and specificity was 94.8%. The Kappa value for the training set was .923. Application of the proposed method to the testing set (30 records) resulted in a geometric mean of 81.5%. The Kappa value for the testing set was .684. Conclusions Based on the overall performance of the system it can be stated that the proposed methodology is a promising new approach for the feature extraction and classification of FHR signals.
Related Links	https://biomedical-engineering-online.biomedcentral.com/counter/pdf/10.1186/1475-925X-10-6.pdf
Ending Page	15
Page Count	15
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/1475-925X-10-6
Journal	BioMedical Engineering OnLine
Issue Number	1
Volume Number	10
Language	English
Publisher	BioMed Central
Publisher Date	2011-01-19
Access Restriction	Open
Subject Keyword	Biomedical Engineering and Bioengineering Biomaterials Biotechnology Biomedical Engineering Support Vector Machine Support Vector Machine Classifier Empirical Mode Decomposition Fetal Heart Rate Intrinsic Mode Function Biomedical Engineering/Biotechnology
Content Type	Text
Resource Type	Article
Subject	Biomaterials Radiological and Ultrasound Technology Biomedical Engineering Radiology, Nuclear Medicine and Imaging
Journal Impact Factor	2.9/2023
5-Year Journal Impact Factor	3.5/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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