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

Dunn, Jessilyn, et al. “Building an open-source community to enhance autonomic nervous system signal analysis: DBDP-autonomic.” Frontiers in Digital Health 6 (2025): 1467424.

Jessilyn Dunn, Varun Mishra, Md Mobashir Hasan Shandhi, Hayoung Jeong, Natasha Yamane, Yuna Watanabe, Bill Chen, Matthew S Goodwin

This figure demonstrates the need for additional context when analyzing ambulatory physiological signals.

Summary

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.

Citation

Frontiers in Digital Health

BibTex

@article{dunn2025building, title={Building an open-source community to enhance autonomic nervous system signal analysis: DBDP-autonomic}, author={Dunn, Jessilyn and Mishra, Varun and Shandhi, Md Mobashir Hasan and Jeong, Hayoung and Yamane, Natasha and Watanabe, Yuna and Chen, Bill and Goodwin, Matthew S}, journal={Frontiers in Digital Health}, volume={6}, pages={1467424}, year={2025} }

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