AUDAPRET: Towards a cloud architecture supporting multi-device research studies

Nadine Von Frankenberg, Felix Matschilles, Stephan Jonas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recent improvements in the functional range and measurement accuracy of commercially available biosignal measurement devices enable cost-effective human trials with large numbers of participants. Biosignals can be tracked outside the research institution, with only minor restrictions in the daily activities of the study participants, compared to stationary measuring devices. However, there is a lack of data acquisition systems supporting the use of several different devices needed, so that the collected data from measurement devices have to be processed manually. Researchers must also abide by strict legal regulations when handling health-related data of study participants, which is often cumbersome and requires additional time-consuming efforts. To address these challenges, this paper proposes the AUtomatic DAta Processing of REsearch Trials (AUDAPRET) architecture, which enables researchers to conduct trials requiring health-related data of participants in a less time-consuming and legally compliant manner. AUDAPRET is designed in such a way that study participants retain full control over their data and the access rights of anyone requesting access.

Original languageEnglish
Title of host publicationProceedings of the 12th IADIS International Conference e-Health 2020, EH 2020 - Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020
PublisherIADIS
Pages209-212
Number of pages4
ISBN (Electronic)9789898704184
StatePublished - 2020
Event12th IADIS International Conference e-Health 2020, EH 2020, Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020 - Virtual, Online
Duration: 21 Jul 202023 Jul 2020

Publication series

NameProceedings of the 12th IADIS International Conference e-Health 2020, EH 2020 - Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020

Conference

Conference12th IADIS International Conference e-Health 2020, EH 2020, Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020
CityVirtual, Online
Period21/07/2023/07/20

Keywords

  • Data Collection
  • EHealth Architectures
  • Health Information Systems
  • Human Study Management

Fingerprint

Dive into the research topics of 'AUDAPRET: Towards a cloud architecture supporting multi-device research studies'. Together they form a unique fingerprint.

Cite this