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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

References

  1. Abeler, K., Bergvik, S., Sand, T., & Friborg, O. (2021). Daily associations between sleep and pain in patients with chronic musculoskeletal pain. J Sleep Res, 30(4). DOI: 10.1111/jsr.13237
    Open DOISearch in Google ScholarBack to article
  2. Atkinson, J. H., Ancoli-Israel, S., Slater, M. A., Garfin, S. R., & Gillin, C. (1988). Subjective Sleep Disturbance in Chronic Back Pain. Clin J Pain, 4(4), 225. DOI: 10.1097/00002508-198812000-00007
    Open DOISearch in Google ScholarBack to article
  3. Centers for Disease Control and Prevention. (2023). NHANES – National Health and Nutrition Examination Survey Homepage. Accessed April 11, 2023. https://www.cdc.gov/nchs/nhanes/index.htm
    Search in Google ScholarBack to article
  4. Chung, K. F., & Tso, K. C. (2010). Relationship between insomnia and pain in major depressive disorder: A sleep diary and actigraphy study. Sleep Med, 11(8), 752–758. DOI: 10.1016/j.sleep.2009.09.005
    Open DOISearch in Google ScholarBack to article
  5. Crombez, G., Vlaeyen, J. W. S., Heuts, P. H. G., & Lysens, R. (1999). Pain-related fear is more disabling than pain itself: evidence on the role of pain-related fear in chronic back pain disability. Pain, 80(1), 329–339. DOI: 10.1016/S0304-3959(98)00229-2
    Open DOISearch in Google ScholarBack to article
  6. Domelen, D. R. V. (2018). Accelerometry: Functions for Processing Accelerometer Data. Published online August 24, 2018. Accessed April 11, 2023. https://CRAN.R-project.org/package=accelerometry
    Search in Google ScholarBack to article
  7. Fisher, K., Laikin, A. M., Sharp, K. M. H., Criddle, C. A., Palermo, T. M., & Karlson, C. W. (2018). Temporal relationship between daily pain and actigraphy sleep patterns in pediatric sickle cell disease. J Behav Med, 41(3), 416–422. DOI: 10.1007/s10865-018-9918-7
    Open DOISearch in Google ScholarBack to article
  8. Grunberg, V. A., Greenberg, J., Mace, R. A., Bakhshaie, J., Choi, K. W., & Vranceanu, A. M. (2022). Fitbit Activity, Quota-Based Pacing, and Physical and Emotional Functioning Among Adults With Chronic Pain. J Pain, 23(11), 1933–1944. DOI: 10.1016/j.jpain.2022.07.003
    Open DOISearch in Google ScholarBack to article
  9. Heinz, M. V., Price, G. D., & Ruan, F., et al. (2022). Association of Selective Serotonin Reuptake Inhibitor Use With Abnormal Physical Movement Patterns as Detected Using a Piezoelectric Accelerometer and Deep Learning in a Nationally Representative Sample of Noninstitutionalized Persons in the US. JAMA Netw Open, 5(4), e225403. DOI: 10.1001/jamanetworkopen.2022.5403
    Open DOISearch in Google ScholarBack to article
  10. Herr, K., Coyne, P. J., McCaffery, M., Manworren, R., & Merkel, S. (2011). Pain Assessment in the Patient Unable to Self-Report: Position Statement with Clinical Practice Recommendations. Pain Manag Nurs, 12(4), 230–250. DOI: 10.1016/j.pmn.2011.10.002
    Open DOISearch in Google ScholarBack to article
  11. Hodges, P. W., Coppieters, M. W., MacDonald, D., & Cholewicki, J. (2013). New insight into motor adaptation to pain revealed by a combination of modeling and empirical approaches: New insight into motor adaptation to pain. Eur J Pain, 17(8), 1138–1146. DOI: 10.1002/j.1532-2149.2013.00286.x
    Open DOISearch in Google ScholarBack to article
  12. Insel, T. R. (2017). Digital Phenotyping: Technology for a New Science of Behavior. JAMA, 318(13), 1215–1216. DOI: 10.1001/jama.2017.11295
    Open DOISearch in Google ScholarBack to article
  13. Institute of Medicine (US) Committee on Advancing Pain Research, Care, and Education. (2011). Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research. National Academies Press (US); 2011. Accessed January 16, 2023. http://www.ncbi.nlm.nih.gov/books/NBK91497/
    Search in Google ScholarBack to article
  14. Jacobson, N. C., & O’Cleirigh, C. (2021). Objective digital phenotypes of worry severity, pain severity and pain chronicity in persons living with HIV. Br J Psychiatry, 218(3), 165–167. DOI: 10.1192/bjp.2019.168
    Open DOISearch in Google ScholarBack to article
  15. Kichline, T., Cushing, C. C., Ortega, A., Friesen, C., & Schurman, J. V. (2019). Associations Between Physical Activity and Chronic Pain Severity in Youth With Chronic Abdominal Pain. Clin J Pain, 35(7), 618–624. DOI: 10.1097/AJP.0000000000000716
    Open DOISearch in Google ScholarBack to article
  16. Kori, S. H. (1990). Kinesiophobia : a new view of chronic pain behavior. Pain Manage. (3), 35–43.
    Search in Google ScholarBack to article
  17. Kozey, S. L., Staudenmayer, J. W., Troiano, R. P., & Freedson, P. S. (2010). Comparison of the ActiGraph 7164 and the ActiGraph GT1M during Self-Paced Locomotion. Med Sci Sports Exerc, 42(5), 971–976. DOI: 10.1249/MSS.0b013e3181c29e90
    Open DOISearch in Google ScholarBack to article
  18. Lee, J., & Kim, J. (2022). Evaluation of Spatial and Temporal Performance of Deep Learning Models for Travel Demand Forecasting: Application to Bike-Sharing Demand Forecasting. R. G. González-Ramírez (Ed.), J Adv Transp, 2022, 1–13. DOI: 10.1155/2022/5934670
    Open DOISearch in Google ScholarBack to article
  19. Long, A. C., Palermo, T. M., & Manees, A. M. (2007). Brief Report: Using Actigraphy to Compare Physical Activity Levels in Adolescents with Chronic Pain and Healthy Adolescents. J Pediatr Psychol, 33(6), 660–665. DOI: 10.1093/jpepsy/jsm136
    Open DOISearch in Google ScholarBack to article
  20. Lunde, L. H., Pallesen, S., Krangnes, L., & Nordhus, I. H. (2010). Characteristics of Sleep in Older Persons With Chronic Pain: A Study Based on Actigraphy and Self-reporting. Clin J Pain, 26(2), 132. DOI: 10.1097/AJP.0b013e3181b61923
    Open DOISearch in Google ScholarBack to article
  21. Morley, S. (2008). Psychology of pain. British journal of anaesthesia, 101(1), 25–31. DOI: 10.1093/bja/aen123
    Open DOISearch in Google ScholarBack to article
  22. Moseley, G. L., Gallagher, L., & Gallace, A. (2012). Neglect-like tactile dysfunction in chronic back pain. Neurology, 79(4), 327–332. DOI: 10.1212/WNL.0b013e318260cba2
    Open DOISearch in Google ScholarBack to article
  23. Nahin, R. L. (2015). Estimates of Pain Prevalence and Severity in Adults: United States, 2012. J Pain, 16(8), 769–780. DOI: 10.1016/j.jpain.2015.05.002
    Open DOISearch in Google ScholarBack to article
  24. Parker, R., et al. (2017). “Levels of physical activity in people with chronic pain.” South African Journal of Physiotherapy, 73(1), 1–7. DOI: 10.4102/sajp.v73i1.323
    Open DOISearch in Google ScholarBack to article
  25. Rahman, S. A., & Adjeroh, D. A. (2019). Deep Learning using Convolutional LSTM estimates Biological Age from Physical Activity. Sci Rep, 9(1), 11425. DOI: 10.1038/s41598-019-46850-0
    Open DOISearch in Google ScholarBack to article
  26. Sarwar, A., Agu, E. O., Polcari, J., Ciroli, J., Nephew, B., & King, J. (2022). PainRhythms: Machine learning prediction of chronic pain from circadian dysregulation using actigraph data — a preliminary study. Smart Health, 26, 100344. DOI: 10.1016/j.smhl.2022.100344
    Open DOISearch in Google ScholarBack to article
  27. Smith, T. J., & Hillner, B. E. (2019). The Cost of Pain. JAMA Netw Open, 2(4), e191532. DOI: 10.1001/jamanetworkopen.2019.1532
    Open DOISearch in Google ScholarBack to article
  28. Spenkelink, C. D., Hutten, M. M., Hermens, H. J., & Greitemann, B. O. (2002). Assessment of activities of daily living with an ambulatory monitoring system: a comparative study in patients with chronic low back pain and nonsymptomatic controls. Clin Rehabil, 16(1), 16–26. DOI: 10.1191/0269215502cr463oa
    Open DOISearch in Google ScholarBack to article
  29. van den Berg-Emons, R. J., Schasfoort, F. C., de Vos, L. A., Bussmann, J. B., & Stam, H. J. (2007). Impact of chronic pain on everyday physical activity⋆. Eur J Pain, 11(5), 587–593. DOI: 10.1016/j.ejpain.2006.09.003
    Open DOISearch in Google ScholarBack to article
  30. Vlaeyen, J. W. S., Crombez, G., & Goubert, L. (2007). The psychology of chronic pain and its management. Physical Therapy Reviews, 12(3), 179–188. DOI: 10.1179/108331907X223001
    Open DOISearch in Google ScholarBack to article
  31. Vlaeyen, J. W. S., Kole-Snijders, A. M. J., Rotteveel, A. M., Ruesink, R., & Heuts, P. H. T. G. (1995). The role of fear of movement/(re)injury in pain disability. J Occup Rehabil, 5(4), 235–252. DOI: 10.1007/BF02109988
    Open DOISearch in Google ScholarBack to article
  32. Wegier, W., & Ksieniewicz, P. (2020). Application of Imbalanced Data Classification Quality Metrics as Weighting Methods of the Ensemble Data Stream Classification Algorithms. Entropy, 22(8), 849. DOI: 10.3390/e22080849
    Open DOISearch in Google ScholarBack to article
  33. Wilson, A. C., & Palermo, T. M. (2012). Physical Activity and Function in Adolescents With Chronic Pain: A Controlled Study Using Actigraphy. J Pain, 13(2), 121–130. DOI: 10.1016/j.jpain.2011.08.008
    Open DOISearch in Google ScholarBack to article
DOI: https://doi.org/10.5334/paah.329 | Journal eISSN: 2515-2270
Journal RSS Feed
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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