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PERSPECTIVE article

Front. Digit. Health
Sec. Health Informatics
Volume 6 - 2024 | doi: 10.3389/fdgth.2024.1467424

Building an Open-Source Community to Enhance Autonomic Nervous System Signal Analysis: DBDP-Autonomic

Provisionally accepted
Jessilyn Dunn Jessilyn Dunn 1Varun Mishra Varun Mishra 2*Md Mobashir Hasan Shandhi Md Mobashir Hasan Shandhi 1Hayoung Jeong Hayoung Jeong 1Natasha Yamane Natasha Yamane 2Yuna Watanabe Yuna Watanabe 2Bill Chen Bill Chen 1Matthew S Goodwin Matthew S Goodwin 2
  • 1 Duke University, Durham, North Carolina, United States
  • 2 Northeastern University, Boston, United States

The final, formatted version of the article will be published soon.

    Smartphones and wearable sensors offer an unprecedented ability to collect peripheral psychophysiological signals across diverse timescales, settings, populations, and modalities. However, open-source software development has yet to keep pace with rapid advancements in hardware technology and availability, creating an analytical barrier that limits the scientific usefulness of acquired data. We propose a community-driven, open-source peripheral psychophysiological signal pre-processing and analysis software framework that could advance biobehavioral health by enabling more robust, transparent, and reproducible inferences involving autonomic nervous system data.

    Keywords: physiological signals, Signal processing, autonomic signals, open-source, Psychophysiology, Digital phenotyping

    Received: 19 Jul 2024; Accepted: 16 Dec 2024.

    Copyright: © 2024 Dunn, Mishra, Shandhi, Jeong, Yamane, Watanabe, Chen and Goodwin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Varun Mishra, Northeastern University, Boston, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.