A Linear Time Series Analysis of Fetal Heart Rate to Detect the Variability: Measures Using Cardiotocography

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Author(s): Sahana Das (Narula Institute of Technology, India), Kaushik Roy (West Bengal State University, India)and Chanchal Kumar Saha (Biraj Mohini Matrisadan and Hospital, India)
Copyright: 2017
Pages: 25
Source title: Handbook of Research on Recent Developments in Intelligent Communication Application
Source Author(s)/Editor(s): Siddhartha Bhattacharyya (RCC Institute of Information Technology, India), Nibaran Das (Jadavpur University, India), Debotosh Bhattacharjee (Jadavpur University, India)and Anirban Mukherjee (RCC Institute of Information Technology, India)
DOI: 10.4018/978-1-5225-1785-6.ch018

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference / Networking and Telecommunications

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Abstract

Real time analysis and interpretation of fetal heart rate (FHR) is the challenge posed to every clinician. Different algorithms had been developed, tried and subsequently incorporated into Cardiotocograph (CTG) machines for automated diagnosis. Feature extraction and accurate detection of baseline and its variability has been the focus of this chapter. Algorithms by Dawes and Redman and Ayres-de-Campos have been discussed in this chapter. The authors are pleased to propose an algorithm for extracting the variability of fetal heart. The algorithm's accuracy and degree of agreement with clinician's diagnosis had been established by various statistical methods. This algorithm has been compared with an algorithm proposed by Nidhal and the new algorithm is found to be better at detecting variability in both ante-partum and intra-partum period.

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A Linear Time Series Analysis of Fetal Heart Rate to Detect the Variability: Measures Using Cardiotocography

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