| Low-complexity R-peak detection for ambulatory fetal monitoring. | |
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MedLine Citation:
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PMID: 22735075 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity. |
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Authors:
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Michael J Rooijakkers; Chiara Rabotti; S Guid Oei; Massimo Mischi |
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Publication Detail:
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Type: Journal Article Date: 2012-06-27 |
Journal Detail:
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Title: Physiological measurement Volume: 33 ISSN: 1361-6579 ISO Abbreviation: Physiol Meas Publication Date: 2012 Jul |
Date Detail:
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Created Date: 2012-06-27 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9306921 Medline TA: Physiol Meas Country: England |
Other Details:
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Languages: eng Pagination: 1135-50 Citation Subset: IM |
Affiliation:
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Faculty of Electrical Engineering, University of Technology Eindhoven, 5612 AZ, Eindhoven, The Netherlands. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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