{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T05:34:10Z","timestamp":1778823250310,"version":"3.51.4"},"reference-count":33,"publisher":"American Institute of Mathematical Sciences (AIMS)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MBE"],"published-print":{"date-parts":[[2023]]},"abstract":"<abstract>\n\n\n<sec><title>Objective<\/title><p>Non-invasive fetal ECG (NI-FECG) provides a non-invasive method to monitor the health of the fetus. However, the NI-FECG is easily interfered by noise, which makes the signal quality decline, leading to the fetal heart rate (FHR) monitoring becoming a challenging task.<\/p>\n<\/sec>\n\n\n\n<sec><title>Methods<\/title><p>In this work, an algorithm for dynamic evaluation of signal quality is proposed to improve the multi-channel FHR monitoring. The innovation of the method is to assess the signal quality in the process of multi-channel fetal QRS (FQRS) complexes detection. Specifically, the detected FQRS is used as quality unit. Each quality unit can be a true R peak (TR) or a false R peak (FR). It is the basic quality information in this work. The signal quality of each channel is estimated by estimating the correctness of the detection results. Further, the TRs of all channels can be fused to obtain more reliable fetal heart rate monitoring.<\/p>\n<\/sec>\n\n\n\n<sec><title>Main results<\/title><p>Analysis results demonstrate that the proposed algorithm is capable of selecting the good quality signal for FQRS detection achieving 97.40% $ PPV $, 98.33% $ SE $ and 97.86% $ F_1 $.<\/p>\n<\/sec>\n\n\n\n<sec><title>Significance<\/title><p>This work sheds light on the quality assessment of fetal monitoring signal.<\/p>\n<\/sec>\n\n<\/abstract><\/jats:p>","DOI":"10.3934\/mbe.2023344","type":"journal-article","created":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T11:04:37Z","timestamp":1677150277000},"page":"7943-7956","source":"Crossref","is-referenced-by-count":3,"title":["A signal quality assessment method for fetal QRS complexes detection"],"prefix":"10.3934","volume":"20","author":[{"given":"Wei","family":"Zhong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Mao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2321","reference":[{"key":"key-10.3934\/mbe.2023344-1","doi-asserted-by":"publisher","unstructured":"P. Mannella, L. Billeci, A. Giannini, A. Canu, F. Pancetti, T. Simoncini, et al., A feasibility study on non-invasive fetal ECG to evaluate prenatal autonomic nervous system activity, Eur. J. Obstet. Gyn. R. B.<\/i>, 246<\/b> (2020), 60\u201366. https:\/\/doi.org\/10.1016\/j.ejogrb.2020.01.015","DOI":"10.1016\/j.ejogrb.2020.01.015"},{"key":"key-10.3934\/mbe.2023344-2","doi-asserted-by":"publisher","unstructured":"E. Castillo, D. P. Morales, A. Garc\u00eda, L. Parrilla, V. U. Ruiz, J. A. \u00c1lvarez Bermejo, A clustering-based method for single-channel fetal heart rate monitoring, PLoS One<\/i>, 13<\/b> (2018), 1\u201322. https:\/\/doi.org\/10.1371\/journal.pone.0199308","DOI":"10.1371\/journal.pone.0199308"},{"key":"key-10.3934\/mbe.2023344-3","doi-asserted-by":"publisher","unstructured":"T. L. Yassin, A. R. Esam, Fetal ECG extraction using input-mode and output-mode adaptive filters with blind source separation, IEEE Can. J. Electr. Comput. 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