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Tingginya angka kematian ibu dan bayi di negara berkembang masih menjadi tantangan besar dalam kesehatan masyarakat. Faktor penyebabnya meliputi kemiskinan, infrastruktur kesehatan yang terbatas, dan norma budaya yang membatasi akses layanan kesehatan. Salah satu kendala utama adalah kurangnya pemantauan kesehatan ibu hamil secara kontinu dan real-time, yang menyebabkan keterlambatan deteksi risiko komplikasi kehamilan. Berbagai upaya telah dilakukan, namun masih terdapat kesenjangan dalam penggunaan teknologi yang mampu memantau kondisi kesehatan ibu secara praktis dan akurat di lapangan. Penelitian ini bertujuan mengembangkan perangkat Internet of Things (IoT) untuk mengukur parameter kesehatan ibu hamil, seperti tinggi badan, berat badan, tekanan darah, dan detak jantung janin, dengan pengiriman data secara real-time ke cloud menggunakan Firebase. Pengujian dilakukan pada 15 ibu hamil di Kabupaten Malang, dengan membandingkan hasil pengukuran perangkat IoT terhadap alat ukur standar. Hasil menunjukkan tingkat akurasi tinggi, dengan rata-rata error 0,45% untuk tinggi badan dan 0,29% untuk berat badan. Pengukuran tekanan darah sistolik memiliki variasi error lebih besar (7,71%–21,45%), sedangkan tekanan darah diastolik lebih stabil (1,81%–8,95%). Pengiriman data ke Firebase menunjukkan delay rata-rata antara 1,75 hingga 2,69 detik tanpa kehilangan data, menandakan sistem komunikasi data berjalan optimal dan menjaga integritas informasi. Perangkat IoT ini berpotensi mendukung pemantauan kesehatan ibu hamil secara real-time sehingga mempermudah intervensi medis dini dan berkontribusi menurunkan angka kematian ibu dan bayi di wilayah berkembang.
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References
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References
A. Alkhatib, L. A. Nnyanzi, B. Mujuni, G. Amanya, and C. Ibingira, “Preventing multimorbidity with lifestyle interventions in sub-saharan africa: A new challenge for public health in low and middle-income countries,” Dec. 01, 2021, MDPI. doi: 10.3390/ijerph182312449.
M. L. Thorsen, S. Harris, R. McGarvey, J. Palacios, and A. Thorsen, “Evaluating disparities in access to obstetric services for American Indian women across Montana,” Journal of Rural Health, vol. 38, no. 1, pp. 151–160, Jan. 2022, doi: 10.1111/jrh.12572.
W. Mweteni et al., “Implications of power imbalance in antenatal care seeking among pregnant adolescents in rural Tanzania: A qualitative study,” PLoS One, vol. 16, no. 6 June 2021, Jun. 2021, doi: 10.1371/journal.pone.0250646.
R. Correa-De-Araujo and S. S. Yoon, “Clinical Outcomes in High-Risk Pregnancies Due to Advanced Maternal Age,” J Womens Health, vol. 30, no. 2, pp. 160–167, Feb. 2021, doi: 10.1089/jwh.2020.8860.
L. M. Yee et al., “Association of Health Literacy among Nulliparous Individuals and Maternal and Neonatal Outcomes,” JAMA Netw Open, vol. 4, no. 9, Sep. 2021, doi: 10.1001/jamanetworkopen.2021.22576.
N. A. Almujally et al., “Monitoring Acute Heart Failure Patients Using Internet-of-Things-Based Smart Monitoring System,” Sensors, vol. 23, no. 10, May 2023, doi: 10.3390/s23104580.
J. Y. Wu, Y. Wang, C. T. S. Ching, H. M. D. Wang, and L. De Liao, “IoT-based wearable health monitoring device and its validation for potential critical and emergency applications,” Front Public Health, vol. 11, 2023, doi: 10.3389/fpubh.2023.1188304.
M. R. Islam, M. M. Kabir, M. F. Mridha, S. Alfarhood, M. Safran, and D. Che, “Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time,” Sensors, vol. 23, no. 11, Jun. 2023, doi: 10.3390/s23115204.
M. M. Hossain et al., “Internet of Things in Pregnancy Care Coordination and Management: A Systematic Review,” Dec. 01, 2023, Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/s23239367.
B. B. Morris, B. Rossi, and B. Fuemmeler, “The role of digital health technology in rural cancer care delivery: A systematic review,” Jun. 01, 2022, John Wiley and Sons Inc. doi: 10.1111/jrh.12619.
L. Yang et al., “Changes in Mobile Health Apps Usage Before and After the COVID-19 Outbreak in China: Semilongitudinal Survey,” JMIR Public Health Surveill, vol. 9, 2022, [Online]. Available: https://api.semanticscholar.org/CorpusID:255774433
A. Suh and M. Li, “Digital tracing during the COVID-19 pandemic: User appraisal, emotion, and continuance intention,” Sustainability (Switzerland), vol. 13, no. 2, pp. 1–17, Jan. 2021, doi: 10.3390/su13020608.
H. Xu, L. Zhang, O. Onireti, Y. Fang, W. J. Buchanan, and M. A. Imran, “BeepTrace: Blockchain-Enabled Privacy-Preserving Contact Tracing for COVID-19 Pandemic and beyond,” IEEE Internet Things J, vol. 8, no. 5, pp. 3915–3929, Mar. 2021, doi: 10.1109/JIOT.2020.3025953.
A. Galle et al., “A double-edged sword-telemedicine for maternal care during COVID-19: Findings from a global mixed-methods study of healthcare providers,” BMJ Glob Health, vol. 6, no. 2, Feb. 2021, doi: 10.1136/bmjgh-2020-004575.
I. Al Khatib, A. Shamayleh, and M. Ndiaye, “Healthcare and the Internet of Medical Things: Applications, Trends, Key Challenges, and Proposed Resolutions,” Informatics, vol. 11, no. 3, p. 47, Jul. 2024, doi: 10.3390/informatics11030047.
L. Lu, G. Hu, J. Liu, and B. Yang, “5G NB-IoT System Integrated with High-Performance Fiber Sensor Inspired by Cirrus and Spider Structures,” Advanced Science, vol. 11, no. 18, May 2024, doi: 10.1002/advs.202309894.
H. Wen et al., “Universal Energy Solution for Triboelectric Sensors Toward the 5G Era and Internet of Things,” Advanced Science, vol. 10, no. 22, Aug. 2023, doi: 10.1002/advs.202302009.
C. Landry et al., “A smartphone application toward detection of systolic hypertension in underserved populations,” Sci Rep, vol. 14, no. 1, Dec. 2024, doi: 10.1038/s41598-024-65269-w.
L. Zheng, S. Yang, and X. Zhang, “Doppler effect in TianQin time-delay interferometry,” Physical Review D, vol. 108, no. 2, Jul. 2023, doi: 10.1103/PhysRevD.108.022001.