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Noninvasive Electrocardiography in the Perinatal Mouse
Published on: June 12, 2020
NInFEA: an embedded framework for the real-time evaluation of fetal ECG extraction algorithms
Danilo Pani1, Gianluca Barabino, Luigi Raffo
1DIEE, Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy. pani@diee.unica.it
Biomedizinische Technik. Biomedical Engineering
|January 15, 2013
Summary
This study introduces NInFEA, an embedded system for real-time fetal ECG extraction algorithm evaluation. It bridges the gap between theoretical algorithms and practical hardware implementation for non-invasive fetal electrocardiogram analysis.
Area of Science:
- Biomedical Engineering
- Signal Processing
Background:
- Fetal electrocardiogram (ECG) extraction from non-invasive recordings is a significant research challenge.
- Existing literature lacks details on embedded hardware for real-time fetal ECG analysis, hindering practical application.
Purpose of the Study:
- To present NInFEA (non-invasive fetal ECG analysis), an embedded hardware/software framework.
- To enable real-time evaluation of fetal ECG extraction algorithms on a low-power platform.
Main Methods:
- Developed an embedded framework (NInFEA) using a hybrid dual-core OMAP-L137 processor.
- Utilized a digital signal processor (DSP) for signal processing and a general-purpose processor (GPP) for the user interface.
- Ported three state-of-the-art fetal ECG extraction algorithms onto the NInFEA platform.
Main Results:
- The hybrid dual-core architecture demonstrated superior performance compared to single-core systems.
- NInFEA successfully supported real-time evaluation of advanced fetal ECG extraction algorithms.
- The framework provided clinicians with necessary additional information via a user interface.
Conclusions:
- NInFEA serves as a valuable reference design for non-invasive fetal ECG analysis applications.
- It offers a common embedded, low-power testbed for developing and evaluating real-time fetal ECG extraction algorithms.
