Efficient implementation of LMS adaptive filter-based FECG extraction on an FPGA
| Autor: | Bhavya Vasudeva, Puneesh Deora, Pradhan Mohan Pradhan, Sudeb Dasgupta |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
electrocardiography
least mean squares methods medical signal processing adaptive filters flip-flops field programmable gate arrays obstetrics series architecture existing fpga implementations fecg extraction methods lms adaptive filter-based fecg extraction fpga implementation foetal heart rate monitoring system preprocessing unit foetal electrocardiogram extraction unit fhr detection unit arithmetic operations floating-point unit mean squares lms-af lower utilisation parallel architecture convergence time extracted fecg noninvasive fecg databases Medical technology R855-855.5 |
| Zdroj: | Healthcare Technology Letters (2020) |
| Druh dokumentu: | article |
| ISSN: | 2053-3713 |
| DOI: | 10.1049/htl.2020.0016 |
| Popis: | In this Letter, the field programmable gate array (FPGA) implementation of a foetal heart rate (FHR) monitoring system is presented. The system comprises a preprocessing unit to remove various types of noise, followed by a foetal electrocardiogram (FECG) extraction unit and an FHR detection unit. To improve the precision and accuracy of the arithmetic operations, a floating-point unit is developed. A least mean squares algorithm-based adaptive filter (LMS-AF) is used for FECG extraction. Two different architectures, namely series and parallel, are proposed for the LMS-AF, with the series architecture targeting lower utilisation of hardware resources, and the parallel architecture enabling less convergence time and lower power consumption. The results show that it effectively detects the R peaks in the extracted FECG with a sensitivity of 95.74–100% and a specificity of 100%. The parallel architecture shows up to an 85.88% reduction in the convergence time for non-invasive FECG databases while the series architecture shows a 27.41% reduction in the number of flip flops used when compared with the existing FPGA implementations of various FECG extraction methods. It also shows an increase of 2–7.51% in accuracy when compared to previous works. |
| Databáze: | Directory of Open Access Journals |
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