Prototyping of Fetal QRS Complex Detection Algorithm | Hardware Prototyping of an Efficient Fetal QRS Complex Detection Algorithm for Fetal Heart Rate Monitoring

Md. Mamun Bin Ibne Reaz (u. a.)

ISBN 10: 3847379216 / ISBN 13: 9783847379218

Published by LAP Lambert Academic Publishing, 2012

About this Item

Prototyping of Fetal QRS Complex Detection Algorithm | Hardware Prototyping of an Efficient Fetal QRS Complex Detection Algorithm for Fetal Heart Rate Monitoring | Md. Mamun Bin Ibne Reaz (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783847379218 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106644773

Bibliographic Details

• Title: Prototyping of Fetal QRS Complex Detection Algorithm | Hardware Prototyping of an Efficient Fetal QRS Complex Detection Algorithm for Fetal Heart Rate Monitoring
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3847379216
• ISBN 13: 9783847379218
• Binding: Taschenbuch
• Condition: Neu
• Seller catalogs:
  • Bücher

About this title

Synopsis

Fetal Electrocardiogram (FECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. A Back-propagation Neural Network and Adaptive Linear Neural Network have been designed to extract the FECG from the abdominal ECG to assess the fetus during the pregnancy and labor. The neural network was trained to recognize the normal waveform and filtered out the unnecessary artifacts including noises in the ECG signal, including power line interference, motion artifacts, baseline drift, ECG amplitude modulation with respiration and other composite noises. The performance of the designed algorithm for FHR extraction is 93.75%. The algorithm has been modeled using VHDL for hardware modeling of FHR monitoring system, which has been synthesized and fitted into Altera’s Stratix II EP2S15F484C3 using the Quartus II version 7.2 Web Edition where the logic and DSP block utilization were 89% and 50% respectively. This research will open up a passage to biomedical researchers and physicians to advocate an excellent understanding of FECG signal and its analysis procedures for FHR monitoring system.

About the Author

Mamun Bin Ibne Reaz was born in Bangladesh, in December 1963. He received his Ph.D. in EE from Ibaraki University, Japan. He is currently an Associate Professor in Universiti Kebangsaan Malaysia, Malaysia. His research area is VLSI Design. He is a regular associate of the Abdus Salam International Center for Theoretical Physics.