Preprint has been published in a journal as an article
Preprint / Version 1

Iot-Based Pregnant Mother Contraction Monitoring System Design


Rancang Bangun Sistem Monitoring Kontraksi Ibu Hamil Berbasis Iot

##article.authors##

DOI:

https://doi.org/10.21070/ups.3802

Keywords:

Monitoring Contractions of Pregnant Women, Iot Technology

Abstract

Pregnancy is an important stage in a woman's life that requires special monitoring and care to ensure the well being of both mother and foetus. The presence of uterine contractions is an important indicator of imminent labour, and prompt monitoring is essential to spot difficulties and ensure a safe delivery. This study aims to track contractions in pregnant women to improve prenatal and labour care. Real-time monitoring, recording and analysis of uterine contractions. This research is a type of R&D research with the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation. The result of this tool is that it can precisely track contraction activity and send information to the IoT network. Through an easy-to-use mobile app, this information can be accessed by medical staff
caring for pregnant women and pregnant women themselves. To provide continuous monitoring, provide early notification of alarming changes, and facilitate rapid medical response

Downloads

Download data is not yet available.

References

S. A. Abbas, R. Riaz, S. Z. H. Kazmi, S. S. Rizvi, and S. J. Kwon, “Cause Analysis of Caesarian Sections and Application of Machine Learning Methods for Classification of Birth Data,” IEEE Access, vol. 6, pp. 67555–67561, 2018, doi: 10.1109/ACCESS.2018.2879115.

S. AL-Hagree et al., “Decision Tree based Smart System for Pregnant Women Diagnosis,” in 2022 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE), 2022, pp. 1–6. doi: 10.1109/ITSS-IoE56359.2022.9990953.

G. Wicahyono, A. Setyanto, S. Raharjo, and A. Munandar, “Pregnancy Monitoring Mobile Application User Experience Assessment,” in 2019 International Conference on Information and Communications Technology (ICOIACT), 2019, pp. 872–877. doi: 10.1109/ICOIACT46704.2019.8938446.

H. Allahem and S. Sampalli, “Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour,” Inform Med Unlocked, vol. 20, p. 100404, 2020, doi: https://doi.org/10.1016/j.imu.2020.100404.

A. Bin Queyam, R. K. Meena, S. K. Pahuja, and D. Singh, “An IoT Based Multi-Parameter Data Acquisition System for Efficient Bio-Telemonitoring of Pregnant Women at Home,” in 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2018, pp. 14–15. doi: 10.1109/CONFLUENCE.2018.8442686.

D. Hao et al., “Application of decision tree in determining the importance of surface electrohysterography signal characteristics for recognizing uterine contractions,” Biocybern Biomed Eng, vol. 39, no. 3, pp. 806–813, 2019, doi: https://doi.org/10.1016/j.bbe.2019.06.008.

A. A. Falevskaya and Y. O. Bobrova, “The Development of a Web App for Monitoring Fetal Growth,” in 2022 Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), 2022, pp. 1507–1510. doi: 10.1109/ElConRus54750.2022.9755547.

R. Ramprabhu, S. Suresh, K. Latha, and D. Venkatesh, “Virtual Midwife for Pregnant Women and Alert System,” in 2021 4th International Conference on Computing and Communications Technologies (ICCCT), 2021, pp. 574–579. doi: 10.1109/ICCCT53315.2021.9711892.

B. Wiweko et al., “Jakpros: Reproductive Health Education Application for Pregnant Women,” in 2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS), 2018, pp. 225–229. doi: 10.1109/ICACSIS.2018.8618206.

Y. Gupta, S. Kumar, and V. Mago, “Pregnancy Health Monitoring System based on Biosignal Analysis,” in 2019 42nd International Conference on Telecommunications and Signal Processing (TSP), 2019, pp. 664–667. doi: 10.1109/TSP.2019.8769074.

T. G. Troyee, M. K. Raihan, and M. S. Arefin, “Health Monitoring of Expecting Mothers using Multiple Sensor Approach: ‘Preg Care,’” in 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT), 2020, pp. 77–82. doi: 10.1109/ICAICT51780.2020.9333514.

A. Bagwari and K. Gairola, “An Aid for Health monitoring during pregnancy,” in 2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT), 2021, pp. 805–809. doi: 10.1109/CSNT51715.2021.9509654.

L. L. Weitzel, K. G. Howen, B. M. Sibai, S. P. Chauhan, and B. L. Pineles, “iMOVE: a pilot study of a smartphone based application to encourage ambulation in pregnant Individuals,” Am J Obstet Gynecol MFM, vol. 5, no. 8, p. 101037, 2023, doi: https://doi.org/10.1016/j.ajogmf.2023.101037.

S. Sharma et al., “SwasthGarbh: A Smartphone App for Improving the Quality of Antenatal Care and Ameliorating Maternal-Fetal Health,” IEEE J Biomed Health Inform, vol. 27, no. 6, pp. 2729–2738, 2023, doi: 10.1109/JBHI.2022.3211426.

I. Sulistiyowati and M. Imam Muhyiddin, “Disinfectant Spraying Robot to Prevent the Transmission of the Covid-19 Virus Based on the Internet of Things (IoT),” Journal of Electrical Technology UMY (JET-UMY), vol. 5, no. 2, 2021.

Y. C. Jo, H. N. Kim, W. H. Hwang, H. K. Hong, Y. S. Choi, and S. W. Jung, “Wearable Patch Device for Uterine EMG and Preterm Birth Monitoring Applications,” in TENCON 2018 - 2018 IEEE Region 10 Conference, 2018, pp. 1127–1130. doi: 10.1109/TENCON.2018.8650268.

S. Sarafan et al., “Development of a Home-based Fetal Electrocardiogram (ECG) Monitoring System,” in 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, pp. 7116–7119. doi: 10.1109/EMBC46164.2021.9630827.

Z. Zhang, J. Wu, G. Li, W. Liu, and X. Tang, “Separating fetal ECG from transabdominal electrical signal: An application of AE-UNet3+,” in BIBE 2022; The 6th International Conference on Biological Information and Biomedical Engineering, 2022, pp. 1–5.

B. Wang and J. Saniie, “Fetal Electrocardiogram Recognition Using Multilayer Perceptron Neural Network,” in 2018 IEEE International Conference on Electro/Information Technology (EIT), 2018, pp. 434–437. doi: 10.1109/EIT.2018.8500232.

R. Ettiyan and V. Geetha, “A Survey of Health Care Monitoring System for Maternity Women Using Internet-of-Things,” in 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), 2020, pp. 1290–1296. doi: 10.1109/ICISS49785.2020.9315950.

K. N. Risnawati, “Gambaran Jenis Persalinan Pada Ibu Bersalin Dengan Corona Virus Disease 19 Di Rumah Sakit Umum Daerah Wangaya Denpasar,” Kebidanan, vol. 1, no. 2, pp. 6–19, 2021.

R. Multajam, W. S. M. Sanjaya, A. Sambas, M. N. Subkhi, and I. Muttaqien, “Desain dan Analisis Electromyography (EMG) serta Aplikasinya dalam Mendeteksi Sinyal Otot,” Al-HAZEN J. Phys., vol. 2, no. 2, pp. 37–47, 2016.

F. T. Abyanto and F. B. Setiawan, “Deteksi Kejenuhan Seluruh Otot Manusia Menggunakan Sensor Emg Berbasis Mikrokontroler Arduino Uno,” pp. 69–74, 2019, doi: 10.5614/sniko.2018.11.

H. H. Abrianto, K. Sari, and I. Irmayani, “Sistem Monitoring Dan Pengendalian Data Suhu Ruang Navigasi Jarak Jauh Menggunakan WEMOS D1 Mini,” J. Nas. Komputasi dan Teknol. Inf., vol. 4, no. 1, pp. 38–49, 2021, doi: 10.32672/jnkti.v4i1.2687.

Posted

2024-01-26