Building an open-source community to enhance autonomic nervous system signal analysis: DBDP-autonomic.

IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES Frontiers in digital health Pub Date : 2025-01-09 eCollection Date: 2024-01-01 DOI:10.3389/fdgth.2024.1467424
Jessilyn Dunn, Varun Mishra, Md Mobashir Hasan Shandhi, Hayoung Jeong, Natasha Yamane, Yuna Watanabe, Bill Chen, Matthew S Goodwin
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Abstract

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.

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CiteScore
4.20
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0.00%
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0
审稿时长
13 weeks
期刊最新文献
A novel machine learning based framework for developing composite digital biomarkers of disease progression. Building an open-source community to enhance autonomic nervous system signal analysis: DBDP-autonomic. Cyber-bioethics: the new ethical discipline for digital health. Augmented Reality for extremity hemorrhage training: a usability study. Data Report: Educational pathway addressing food and nutrition in amyotrophic lateral sclerosis on the AVASUS platform.
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