Evidence map›Paper›PMID 40987964›Full record

ReviewMedical & biological engineering & computing2026

Pain assessment and determination methods with wearable sensors: a scoping review.

Beren Semiz, Özge Kartin Hancioglu, Remziye Semerci Şahin

Abstract readScoping ReviewReview
PubMed Publisher
In one paragraph

Review in Medical & biological engineering & computing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Beren SemizElectrical and Electronics Engineering, Koc University, Rumelifeneri, 34450, Istanbul, Turkey.
Özge Kartin HanciogluBiomedical Sciences and Engineering, Koc University, Rumelifeneri, 34450, Istanbul, Turkey.
Remziye Semerci ŞahinSchool of Nursing, Koc University, Davutpasa, 34010, Istanbul, Turkey. rsemerci@ku.edu.tr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is no gold standard for objectively measuring pain; wearable devices cannot claim to measure pain itself, but may offer correlational insights through physiological signals. This scoping review synthesizes current evidence on pain-related assessment methods using wearable sensors across pediatric and adult populations. This review followed the PRISMA-ScR guidelines. A systematic literature search was conducted across PubMed, Cochrane Library, Scopus, Web of Science, CINAHL, and Ovid MEDLINE for studies published up to December 2024. A total of 24 studies met the inclusion criteria. The most used wearable devices included commercially available smartwatches, wristbands, and multisensor platforms. Physiological indicators associated with pain responses included heart rate, heart rate variability, electrocardiography, electrodermal activity, electromyography, surface electromyography, photoplethysmography, skin temperature, and electroencephalography, reflecting autonomic, muscular, and neural system activity. Wearable sensors represent a promising, non-invasive tool for capturing physiological pain-related responses, particularly in contexts where verbal self-report is not feasible. While these devices may support more responsive and continuous pain monitoring, they cannot replace self-report measures and should not be interpreted as providing objective pain measurements.

Indexed as

PainPain MeasurementWearable Electronic DevicesAdultChildElectromyographyHeart RateHumansPainPhysiological markersWearable sensors

Identifiers

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.