ArticleBMC pregnancy and childbirth2024
Design and analysis of a telemonitoring system for high-risk pregnant women in need of special care or attention.
Article in BMC pregnancy and childbirth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Unlocking the Adoption of a Smartphone Application for High-Risk Pregnant Women in the Lao People's Democratic Republic: A Mixed-Methods Study.Journal of advanced nursing · 2026Article
- A large scale statistical analysis of quantum and classical neural networks in the medical domain.Scientific reports · 2026Article
- Developing a Data Trust Model (Not Only) for Sleep Research: Conceptual Study and Quantitative Survey.JMIR human factors · 2025Article
- Hierarchical attention mechanism combined with deep neural networks for accurate semantic segmentation of dental structures in panoramic radiographs.Scientific reports · 2025Article
- A novel hybrid attention based deep learning framework for textual emotion recognition using natural language processing technologies for disabled persons.Scientific reports · 2025Article
- Transfer learning driven fake news detection and classification using large language models.Scientific reports · 2025Article
- Unveiling the potential of artificial intelligence in revolutionizing disease diagnosis and prediction: a comprehensive review of machine learning and deep learning approaches.European journal of medical research · 2025Review
- Prediction of high-risk pregnancy based on machine learning algorithms.Scientific reports · 2025Article
- Criminal emotion detection framework using convolutional neural network for public safety.Scientific reports · 2025Article
- Robust emotion recognition for complex environments: ChildEmoNet model based on DETR-ResNet50 cascaded architecture.PloS one · 2025Article
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5 authors.
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Abstract
backgroundHigh-risk pregnancies, characterized by underlying health issues or unusual circumstances, pose increased risks to both maternal and neonatal health during pregnancy and childbirth. Global guidelines emphasize the importance of early identification, monitoring, and intervention to mitigate these risks.
methodWe decided to design and implement a telemonitoring system for remotely monitoring and managing pregnancies in women with conditions such as hypertension, diabetes, or high-risk pregnancy. When a high-risk pregnant mom is discharged from the hospital, the Healthcare Center or Integrated Healthcare Services Center in her area is immediately notified via SMS to ensure her condition is monitored remotely. In addition to sending notifications, the patient's medical record, post-discharge care recommendations, drug prescription, re-visit time, and contact details are also sent to them via the application. The high-risk pregnant mom is followed up and all her information is recorded in the application for further use. To evaluate the usability of the proposed telemonitoring system, we conducted a laboratory study involving 92 participants, including pregnant mothers' care experts at hospitals, healthcare center experts, midwives at integrated healthcare services centers, and midwifery department experts with varying levels of digital skills. Participants performed activities related to the application's services, while their satisfaction was measured using the QUIS 7.0 questionnaires covering multiple aspects of usability, including user interface, system capabilities, and online help, with ratings on a Likert scale.
resultThe usability evaluation revealed that the average satisfaction score across all usability dimensions was above 8, demonstrating a satisfactory level of system usage from all user perspectives. Additionally, the close alignment of mean and median scores, along with standard deviations below 1 for several dimensions, indicated consistent positive feedback among users.
conclusionOur telemonitoring system demonstrates promise for enhancing the management of high-risk pregnancies, facilitating better health outcomes for mothers and infants through effective remote monitoring and support. The usability test results underscore the platform's effectiveness and user satisfaction, contributing valuable insights for future improvements in high-risk pregnancy care.
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