ReviewSensors (Basel, Switzerland)2025
Review of Non-Invasive Fetal Electrocardiography Monitoring Techniques.
Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on AI-driven noninvasive fetal ECG processing and analysis methods.Frontiers in digital health · 2026Pooled it
- Explainable and High-Performance ECG-Informed Machine Learning and Deep Learning Framework for Cardiovascular Risk Prediction.Life (Basel, Switzerland) · 2026Article
- A Deep Learning-Guided Ensemble Empirical Mode Decomposition Method for Single-Channel Fetal Electrocardiogram Extraction.Sensors (Basel, Switzerland) · 2026Article
- A novel multi-step adaptive Kalman filtering method based on dynamic noise estimation for FECG extraction.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Non-invasive fetal electrocardiography (NIFECG), an emerging technology for fetal health monitoring, has garnered significant attention in recent years. It is considered a promising alternative to traditional Doppler ultrasound methods and has the potential to become the standard approach for fetal monitoring. This paper provides a comprehensive review of the latest advancements in NIFECG technology, including signal acquisition, signal preprocessing, fetal electrocardiogram extraction, and fetal cardiac anomaly classification. Furthermore, the characteristics and limitations of existing NIFECG datasets are analyzed, and improvement suggestions are proposed. Future research directions for NIFECG technology are discussed, with a particular focus on the potential applications of deep learning techniques, multimodal data fusion, and remote monitoring systems. This review offers references and support for advancing the development and application of NIFECG monitoring technology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.