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Wearable Movement Data as a Potential Digital Biomarker for Chronic Pain: An Investigation Using Deep Learning Cover

Wearable Movement Data as a Potential Digital Biomarker for Chronic Pain: An Investigation Using Deep Learning

Physical Activity and Health
Volume 8 (2024): Issue 1
By: Hannah Dorris,  Jenny Oh and  Nicholas Jacobson  
Open Access
|Apr 2024

Authors

Hannah Dorris

hannah.j.dorris.gr@dartmouth.edu

Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH; Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, NH

Jenny Oh

jenny.y.oh.25@dartmouth.edu

Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH

Nicholas Jacobson

Nicholas.C.Jacobson@dartmouth.edu

Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH; Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, NH; Department of Psychiatry, Geisel School of Medicine, Dartmouth College, Hanover, NH
DOI: https://doi.org/10.5334/paah.329 | Journal eISSN: 2515-2270
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Language: English
Submitted on: Dec 22, 2023
|
Accepted on: Mar 1, 2024
|
Published on: Apr 25, 2024
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Deep learning,
Chronic pain,
Actigraphy,
Digital tools,
Physical activity,
Passive Sensing

© 2024 Hannah Dorris, Jenny Oh, Nicholas Jacobson, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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