Evidence map›Paper›PMID 41332997›Full record

ArticleProceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference)2025

The Fifth Edition of the Automated Assessment of Pain (AAP 2025).

Zakia Hammal, Steffen Walter, Nadia Bianchi-Berthouze

Abstract read
In one paragraph

Article in Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zakia HammalRobotics Institute, Carnegie Mellon University, Pittsburgh, USA.
Steffen WalterUniversity Hospital Ulm, Ulm, Germany.
Nadia Bianchi-BerthouzeInteraction Centre, University College London, London, United Kingdom.

Funding

Efficient and Cost-Effective Multimodal System for Pain Management in Low Back PainR01NR018451 · NINR · CARNEGIE-MELLON UNIVERSITY · PI HAMMAL, ZAKIA · 2020 to 2025
$2.9M
NINR NIH HHS R01 NR018451
6 · The paper itself

Abstract

Pain communication varies significantly among individuals, some are highly expressive, while others demonstrate stoic restraint and offer minimal verbal indication of discomfort. Substantial progress has been made in identifying behavioral indicators of pain. A growing body of literature highlights measurable indices of pain through facial expressions, vocalizations, body movements, as well as physiological and neural responses. To enhance the reliability of pain monitoring, automated pain assessment has emerged as a promising approach. Although available datasets remain limited, they are steadily increasing, helping to drive research forward. Despite notable progress, this field is still in its early stages. The 5

Indexed as

Clinical DatasetsHealth InformaticsHuman Centered ComputingPain

Identifiers

PMID41332997
PMCPMC12667020

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.