Translating Fetal Electrical Signals into Mechanical Evidence

Abstract

What evidence is needed to determine which mechanical waveform features can be reconstructed from electrical signals and which uncertainty must remain visible? This review answers by treating cross-modal physiological translation as a property of a sociotechnical workflow rather than a feature that can be read from average accuracy. The focal setting is fetal monitoring that relates fetal and maternal electrocardiograms to Doppler mechanical waveforms, where an apparently precise prediction can reflect a split, batch effect, proxy, or measurement artifact rather than a transferable biomedical relation. Evidence from the assigned publications is synthesized with foundational studies of calibration, distribution shift, causal structure, and responsible deployment. Four requirements follow: preserve the lineage of physiological signals, molecular profiles, cohort metadata, labels, model outputs, and independent validation evidence; measure stability across relevant perturbations; connect confidence to a specific action; and maintain a route for human challenge and correction. The framework distinguishes descriptive performance from decision utility and separates uncertainty about the world from uncertainty created by the model and its evaluator. It also shows why faster inference or richer reasoning is valuable only when it improves a defined decision under a transparent resource budget. The article is a literature review and research agenda, not a report of a newly completed trial.