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An Architecture to Support Real-World Studies that Investigate the Autonomic Nervous System

Publication ,  Conference
Groat, D; Gouripeddi, R; Madsen, R; Lin, YK; Facelli, JC
Published in: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics
January 1, 2019
Published version (DOI)

Diabetes is a chronic disease with complications related to the autonomic nervous system (ANS) that can affect quality of life and lead to mortality. Clinicians and researchers currently rely on subjective and/or invasive means that don’t necessarily translate to real-world setting when assessing severity of certain diabetes complications. We elicited use-cases of studies aimed at understanding ANS in the context of diabetes to gather system requirements for designing an architecture to support sensor-based studies. Real-world studies would need to be capable of gathering contextual data as well as proxies for ANS symptoms from digital markers from an evolving sensor landscape, while also supporting the data needs of researchers before, during, and after data acquisition. The proposed architecture makes use of open source and commercially available mobile health technologies, and informatics platforms to meet the design criteria. Building and testing a prototype of the proposed architecture is planned to confirm the system performs as expected.

Duke Scholars

Julio Cesar Facelli
Author Julio Cesar Facelli Biostatistics & Bioinformatics, Division of Translational Bi ...

Published In

Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

DOI

10.1007/978-3-030-33752-0_14

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2019

Volume

11721 LNCS

Start / End Page

196 / 203

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Groat, D., Gouripeddi, R., Madsen, R., Lin, Y. K., & Facelli, J. C. (2019). An Architecture to Support Real-World Studies that Investigate the Autonomic Nervous System. In Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics (Vol. 11721 LNCS, pp. 196–203). https://doi.org/10.1007/978-3-030-33752-0_14
Groat, D., R. Gouripeddi, R. Madsen, Y. K. Lin, and J. C. Facelli. “An Architecture to Support Real-World Studies that Investigate the Autonomic Nervous System.” In Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11721 LNCS:196–203, 2019. https://doi.org/10.1007/978-3-030-33752-0_14.
Groat D, Gouripeddi R, Madsen R, Lin YK, Facelli JC. An Architecture to Support Real-World Studies that Investigate the Autonomic Nervous System. In: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 2019. p. 196–203.
Groat, D., et al. “An Architecture to Support Real-World Studies that Investigate the Autonomic Nervous System.” Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 11721 LNCS, 2019, pp. 196–203. Scopus, doi:10.1007/978-3-030-33752-0_14.
Groat D, Gouripeddi R, Madsen R, Lin YK, Facelli JC. An Architecture to Support Real-World Studies that Investigate the Autonomic Nervous System. Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 2019. p. 196–203.

Published In

Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

DOI

10.1007/978-3-030-33752-0_14

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2019

Volume

11721 LNCS

Start / End Page

196 / 203

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences