Evidence map›Paper›PMID 33540608›Full record

ArticleSensors (Basel, Switzerland)2021

On the Use of Movement-Based Interaction with Smart Textiles for Emotion Regulation.

Mengqi Jiang, Vijayakumar Nanjappan, Martijn Ten Bhömer, Hai-Ning Liang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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

4 authors.

Mengqi JiangDepartment of Computing, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.ORCID 0000-0003-0344-9826
Vijayakumar NanjappanCenter for Ubiquitous Computing, University of Oulu, 90570 Oulu, Finland.ORCID 0000-0001-6081-2826
Martijn Ten BhömerFaculty of Science and Engineering, University of Nottingham Ningbo, Ningbo 315000, China.
Hai-Ning LiangDepartment of Computing, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.ORCID 0000-0003-3600-8955

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research from psychology has suggested that body movement may directly activate emotional experiences. Movement-based emotion regulation is the most readily available but often underutilized strategy for emotion regulation. This research aims to investigate the emotional effects of movement-based interaction and its sensory feedback mechanisms. To this end, we developed a smart clothing prototype, E-motionWear, which reacts to four movements (elbow flexion/extension, shoulder flexion/extension, open and closed arms, neck flexion/extension), fabric-based detection sensors, and three-movement feedback mechanisms (audio, visual and vibrotactile). An experiment was conducted using a combined qualitative and quantitative approach to collect participants' objective and subjective emotional feelings. Results indicate that there was no interaction effect between movement and feedback mechanism on the final emotional results. Participants preferred vibrotactile and audio feedback rather than visual feedback when performing these four kinds of upper body movements. Shoulder flexion/extension and open-closed arm movements were more effective for improving positive emotion than elbow flexion/extension movements. Participants thought that the E-motionWear prototype were comfortable to wear and brought them new emotional experiences. From these results, a set of guidelines were derived that can help frame the design and use of smart clothing to support users' emotional regulation.

Indexed as

Elbow JointEmotional RegulationTextilesAdolescentAdultArmFemaleHumansMaleMovementYoung Adultemotion regulationfeedback mechanisminteractive textilesmovement-based interactionsmart textiles

Identifiers

PMID33540608
PMCPMC7867248

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.