FHIR up Ubicomp Data: Mastering Usability, Common Metrics, FAIRness, and Privacy

Lopera Gonzalez LI, Nguyen TBD, Pryss R, Baumeister H, Amft O (2024)

Publication Type: Journal article

Publication year: 2024

Journal

IEEE Pervasive Computing Institute of Electrical and Electronics Engineers (IEEE)

DOI: 10.1109/MPRV.2024.3486930

Abstract

We propose and analyze a schema to harmonize data and metadata encoding for wearable and ubiquitous devices based on the Fast Healthcare Interoperability Resources standard. Currently, the lack of dataset encoding standards contributes to interpretation errors and proprietary implementations. Our proposed schema describes sensor devices, assessment data, and their characteristics. We develop and evaluate our schema regarding usability, common metric support, FAIRness, and privacy, using four stress monitoring datasets.

Authors with CRIS profile

Luis Ignacio Lopera Gonzalez Professur für Digital Health

Involved external institutions

Universität Ulm DE Germany (DE) Julius-Maximilians-Universität Würzburg DE Germany (DE) Albert-Ludwigs-Universität Freiburg DE Germany (DE)

How to cite

APA:

Lopera Gonzalez, L.I., Nguyen, T.B.D., Pryss, R., Baumeister, H., & Amft, O. (2024). FHIR up Ubicomp Data: Mastering Usability, Common Metrics, FAIRness, and Privacy. IEEE Pervasive Computing. https://doi.org/10.1109/MPRV.2024.3486930

MLA:

Lopera Gonzalez, Luis Ignacio, et al. "FHIR up Ubicomp Data: Mastering Usability, Common Metrics, FAIRness, and Privacy." IEEE Pervasive Computing (2024).

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