25–29 May 2026
La Biodola - Isola d'Elba (Italy)
Europe/Rome timezone
Reminder: Posters are requested to be uploaded by Thursday, 21 May.

Data Acquisition Architecture in TELE-NEURART project

28 May 2026, 18:50
20m
Maria Luisa Room (Hotel Hermitage)

Maria Luisa Room

Hotel Hermitage

Oral presentation Data Acquisition and Trigger Architectures Data Acquisition and Trigger Architectures

Speaker

Dr Donato Romano (Istituto Nazionale di Fisica Nucleare - Sezione di Bari, Bari, Italy)

Description

TELE-NEURART is an Italian-scale virtual paediatric network aimed at advancing the management of neurodevelopmental disorders through (i) tele-monitoring in ecologically valid home settings, (ii) remote telerehabilitation protocols, and (iii) AI-driven identification of digital biomarkers to support personalised yet nationally standardisable care pathways. The network connects specialised centres across Italian regions and relies on a shared research infrastructure for protocol harmonisation and data-driven clinical translation.
This paper presents the Data Acquisition Architecture designed to enable real-time, multi-site acquisition, integration, and processing of heterogeneous clinical and digital data. The DAA targets key challenges typical of paediatric distributed deployments: (1) data heterogeneity across imaging and diagnostic devices, robotic/telerehabilitation platforms, multimodal sensors and structured clinical forms; (2) semantic and technical interoperability, addressed through normalisation and harmonisation workflows and mapping to recognised clinical/functional frameworks, enabling aggregation and reproducible analytics; (3) multi-tier data lifecycle management, combining local storage and local analytics for quality control and pre-processing at the edge, latency reduction for monitoring, and sustainable synchronisation toward federated/central repositories; (4) robustness in real-world contexts, mitigating missing data, noise, device drift, and temporal misalignment via validation, metadata management, device/protocol versioning, time synchronisation, and buffering; and (5) privacy and governance by design, integrating pseudonymisation/anonimisation, access control, audit logging, consent governance, and secure data handling, which are critical for clinical data from minors.
Overall, the proposed DAA provides an AI-ready foundation supporting traceable pipelines from raw signals to curated datasets and derived features, enabling scalable development and validation of clinically actionable digital biomarkers within a distributed paediatric care ecosystem

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Author

Dr Donato Romano (Istituto Nazionale di Fisica Nucleare - Sezione di Bari, Bari, Italy)

Co-authors

Dr Pierfrancesco Novielli (Istituto Nazionale di Fisica Nucleare - Sezione di Bari, Bari, Italy) Pierpaolo Di Bitonto (Università degli Studi di Bari Aldo Moro) Prof. Sabina Tangaro (Istituto Nazionale di Fisica Nucleare - Sezione di Bari, Bari, Italy)

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