Work place: Dept. of Electrical and Electronic Engineering, Federal University of Technology, Minna, Nigeria
E-mail: a.ashraf@futminna.edu.ng
Website:
Research Interests: Image Processing, Swarm Intelligence, Artificial Intelligence, Computer systems and computational processes
Biography
Ashraf A. Ahmad, is a Lecturer at the Federal University of Technology, Minna. He graduated from Bayero University, Kano in 2011 and UniversitiTeknologi Malaysia in 2014, obtaining B.Eng and M.Eng Electrical Engineering respectively. He received the best student award for his master’s program. His research interests include digital signal processing and electronic intelligence. He has a number of publications both in international conferences and journals in the area of his interests.
By Ashraf Adamu Ahmad Aminu Inuwa Kuta Abdulmumini Zubairu Loko
DOI: https://doi.org/10.5815/ijigsp.2017.02.03, Pub. Date: 8 Feb. 2017
This paper presents a method for fetal heart rate estimation from an abdominal electrocardiogram (ECG) signal based on adaptive filter analysis using least mean square (LMS) adaptive filtering algorithm in order to determine the health status of a baby in its mother's womb. The fetal ECG signal is extracted from abdominal ECG containing other sources of interference using the maternal ECG signal obtained from mother's chest cavity as the reference signal. Interference/noise model used for this work include the power-line noise, the white noise and the unwanted propagating maternal ECG signal. Thereafter, the heart rate is estimated using an automated peak voltage measurement algorithm at 75 percent threshold voltage. It is found that irrespective of the estimated heart rate of the baby, 100 percent estimation is achieved at signal-to-noise ratio (SNR) greater than or equal to -31dB.
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