Evidence map›Paper›PMID 34056519›Full record

ReviewDigital biomarkers

Wearable Devices: Current Status and Opportunities in Pain Assessment and Management.

Andrew Leroux, Rachael Rzasa-Lynn, Ciprian Crainiceanu, Tushar Sharma

Abstract readReview
In one paragraph

Review in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed.

  1. Trial
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  4. Observational
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  8. Article
  9. General Innovations in Pain Management.Journal of clinical medicine · 2025
    Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Observational
  15. Review
  16. Article
  17. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Andrew LerouxDepartment of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA.
Rachael Rzasa-LynnDepartment of Anesthesiology, University of Colorado, Aurora, Colorado, USA.
Ciprian CrainiceanuDepartment of Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA.
Tushar SharmaDepartment of Anesthesiology, University of Colorado, Aurora, Colorado, USA.

Funding

EPIDEMIOLOGY AND BIOSTATISTICS OF AGINGT32AG000247 · NIA · JOHNS HOPKINS UNIVERSITY · PI Karen J. Bandeen-Roche · 1996 to 2026
$13.2M
NIA NIH HHS T32 AG000247
6 · The paper itself

Abstract

introductionWe investigated the possibilities and opportunities for using wearable devices that measure physical activity and physiometric signals in conjunction with ecological momentary assessment (EMA) data to improve the assessment and treatment of pain.

methodsWe considered studies with cross-sectional and longitudinal designs as well as interventional or observational studies correlating pain scores with measures derived from wearable devices. A search was also performed on studies that investigated physical activity and physiometric signals among patients with pain.

resultsFew studies have assessed the possibility of incorporating wearable devices as objective tools for contextualizing pain and physical function in free-living environments. Of the studies that have been conducted, most focus solely on physical activity and functional outcomes as measured by a wearable accelerometer. Several studies report promising correlations between pain scores and signals derived from wearable devices, objectively measured physical activity, and physical function. In addition, there is a known association between physiologic signals that can be measured by wearable devices and pain, though studies using wearable devices to measure these signals and associate them with pain in free-living environments are limited.

conclusionThere exists a great opportunity to study the complex interplay between physiometric signals, physical function, and pain in a real-time fashion in free-living environments. The literature supports the hypothesis that wearable devices can be used to develop reproducible biosignals that correlate with pain. The combination of wearable devices and EMA will likely lead to the development of clinically meaningful endpoints that will transform how we understand and treat pain patients.

Indexed as

AccelerometryEcological momentary assessmentmHealthPainPhysical functionWearable devices

Identifiers

PMID34056519
PMCPMC8138140

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.