Clinical perspectives on wearable devices for paediatric cyanotic congenital heart disease: an expert survey to inform the early development of a multiparametric wearable biosensor

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Authors: Roberta Nossa, Emilia Biffi
Cited by: 0

Abstract

This dataset contains responses from a structured survey conducted as part of the OrphaDev4Kids European project (EU4H-2023-PJ), aimed at informing the early-stage development of wearable medical devices for paediatric populations. The survey targeted clinicians with professional experience in managing or studying cyanotic congenital heart disease (CCHD) and captured information on current monitoring practices, perceived unmet clinical needs, and expectations for novel wearable biosensors. The dataset includes: Professional background of respondents Experience with different types of CCHD Standard clinical monitoring practices (physiological, functional, and biochemical parameters) Perspectives on additional biomarkers and multiparametric monitoring needs Familiarity with and attitudes toward wearable technologies Preferences for data delivery, integration with clinical workflows, and device usability Insights regarding patient compliance, operational feasibility, and institutional readiness This resource provides a foundation for understanding clinician priorities in the design of pediatric medical devices, supporting evidence-based development of patient-centered, non-invasive, and real-time monitoring solutions. All data are anonymized to protect respondent privacy. Please cite the following paper if you use the database: This project has received funding from the European Union’s Horizon Europe Framework Programme under Grant Agreement No. 101161377. This wok was partially funded by the Italian Ministry of Health (Ricerca Corrente 2025/2026 to E. Biffi).

Fields of Study & Subjects

Non-Invasive Vital Sign Monitoring Congenital Heart Disease Studies Wireless Body Area Networks

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 February 2026
Language
EN
Document type
Dataset