Research and development evaluates an IoT device for fetal movement, suggesting potential in reducing perinatal morbidity.
Background: Fetal movement monitoring is an essential indicator of fetal well-being and a critical factor in reducing perinatal morbidity and mortality. Current monitoring methods rely on maternal perception or periodic clinical assessment, which are subjective and may delay detection of complications. Real-time, sensor-based, and IoT-enabled monitoring systems remain limited. Purpose: This study aimed to develop and evaluate a simple, IoT-based fetal movement monitoring device using a flex sensor. Methods: A research and development (R&D) approach with the waterfall model was applied. This approach consisted of requirements analysis, system design, implementation, system testing, and maintenance. The prototype was tested on third-trimester pregnant women, including non-pregnant participants, for specificity testing. Results: The device detected between 14 and 33 fetal movements per hour during one-hour monitoring sessions in pregnant participants. No movements were detected in non-pregnant participants, confirming device specificity. Conclusion: An IoT-based fetal movement monitoring device using a flex sensor was successfully developed and demonstrated acceptable accuracy and specificity. This innovation offers a practical and cost-effective tool to support healthcare providers and pregnant women in early detection of potential pregnancy complications, with a possible impact on reducing perinatal morbidity and mortality.
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Hidayah et al. (2025) studied this question.
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