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Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home
Fetal movement is an important biological index of fetal well-being. Since 2008, we have been developing an original capacitive acceleration sensor and device that a pregnant woman can easily use to record fetal movement by herself at home during sleep. In this study, we report a newly developed aut...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4470661/ https://www.ncbi.nlm.nih.gov/pubmed/26083422 http://dx.doi.org/10.1371/journal.pone.0130503 |
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author | Nishihara, Kyoko Ohki, Noboru Kamata, Hideo Ryo, Eiji Horiuchi, Shigeko |
author_facet | Nishihara, Kyoko Ohki, Noboru Kamata, Hideo Ryo, Eiji Horiuchi, Shigeko |
author_sort | Nishihara, Kyoko |
collection | PubMed |
description | Fetal movement is an important biological index of fetal well-being. Since 2008, we have been developing an original capacitive acceleration sensor and device that a pregnant woman can easily use to record fetal movement by herself at home during sleep. In this study, we report a newly developed automated software system for analyzing recorded fetal movement. This study will introduce the system and compare its results to those of a manual analysis of the same fetal movement signals (Experiment I). We will also demonstrate an appropriate way to use the system (Experiment II). In Experiment I, fetal movement data reported previously for six pregnant women at 28-38 gestational weeks were used. We evaluated the agreement of the manual and automated analyses for the same 10-sec epochs using prevalence-adjusted bias-adjusted kappa (PABAK) including quantitative indicators for prevalence and bias. The mean PABAK value was 0.83, which can be considered almost perfect. In Experiment II, twelve pregnant women at 24-36 gestational weeks recorded fetal movement at night once every four weeks. Overall, mean fetal movement counts per hour during maternal sleep significantly decreased along with gestational weeks, though individual differences in fetal development were noted. This newly developed automated analysis system can provide important data throughout late pregnancy. |
format | Online Article Text |
id | pubmed-4470661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44706612015-06-29 Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home Nishihara, Kyoko Ohki, Noboru Kamata, Hideo Ryo, Eiji Horiuchi, Shigeko PLoS One Research Article Fetal movement is an important biological index of fetal well-being. Since 2008, we have been developing an original capacitive acceleration sensor and device that a pregnant woman can easily use to record fetal movement by herself at home during sleep. In this study, we report a newly developed automated software system for analyzing recorded fetal movement. This study will introduce the system and compare its results to those of a manual analysis of the same fetal movement signals (Experiment I). We will also demonstrate an appropriate way to use the system (Experiment II). In Experiment I, fetal movement data reported previously for six pregnant women at 28-38 gestational weeks were used. We evaluated the agreement of the manual and automated analyses for the same 10-sec epochs using prevalence-adjusted bias-adjusted kappa (PABAK) including quantitative indicators for prevalence and bias. The mean PABAK value was 0.83, which can be considered almost perfect. In Experiment II, twelve pregnant women at 24-36 gestational weeks recorded fetal movement at night once every four weeks. Overall, mean fetal movement counts per hour during maternal sleep significantly decreased along with gestational weeks, though individual differences in fetal development were noted. This newly developed automated analysis system can provide important data throughout late pregnancy. Public Library of Science 2015-06-17 /pmc/articles/PMC4470661/ /pubmed/26083422 http://dx.doi.org/10.1371/journal.pone.0130503 Text en © 2015 Nishihara et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Nishihara, Kyoko Ohki, Noboru Kamata, Hideo Ryo, Eiji Horiuchi, Shigeko Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home |
title | Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home |
title_full | Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home |
title_fullStr | Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home |
title_full_unstemmed | Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home |
title_short | Automated Software Analysis of Fetal Movement Recorded during a Pregnant Woman’s Sleep at Home |
title_sort | automated software analysis of fetal movement recorded during a pregnant woman’s sleep at home |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4470661/ https://www.ncbi.nlm.nih.gov/pubmed/26083422 http://dx.doi.org/10.1371/journal.pone.0130503 |
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