Evidence map›Paper›PMID 41095043›Full record

ArticleSensors (Basel, Switzerland)2025

Gait Variability and Spatiotemporal Parameters During Emotion-Induced Walking: Assessment with Inertial Measurement Units.

Marvin Alvarez, Angeloh Stout, Luke Fisanick, Chuan-Fa Tang, David George Wilson, Leslie Gray, Breanne Logan, Gu Eon Kang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Marvin AlvarezDepartment of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0009-0002-2598-8310
Angeloh StoutDepartment of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA.
Luke FisanickDepartment of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA.
Chuan-Fa TangDepartment of Mathematical Sciences, School of Natural Sciences and Mathematics, The University of Texas at Dallas, Richardson, TX 75080, USA.
David George WilsonDepartment of Prosthetics-Orthotics, School of Health Professions, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.ORCID 0000-0002-3314-9130
Leslie GrayDepartment of Prosthetics-Orthotics, School of Health Professions, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.ORCID 0000-0003-2990-0240
Breanne LoganBrainRobotics, Austin, TX 78758, USA.
Gu Eon KangDepartment of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0000-0002-4791-6839

Funding

Technology Development ComponentP2CHD101899 · NICHD · REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB · PI LIEBER, RICHARD L. · 2020 to 2024
$5.6M
NICHD NIH HHS P2C HD101899
6 · The paper itself

Abstract

Emotion alters the way humans walk, yet most prior studies have relied on laboratory-based 3D motion capture systems. While accurate, these approaches limit translation to real-world settings and have largely focused on spatiotemporal parameters and joint motions. This study evaluated the feasibility of using inertial measurement units (IMUs) to detect emotion-related changes in gait variability as well as spatiotemporal gait parameters. Fourteen healthy young adults completed overground gait trials while wearing two ankle-mounted IMUs. Five target emotions, anger, sadness, neutral emotion, joy, and fear, were elicited using an autobiographical memory paradigm. The IMUs measured stride length, stride time, stride velocity, cadence, and gait variability. The results showed that stride length, stride time, stride velocity, and cadence significantly differed across emotions. Anger and joy were associated with longer strides and faster velocities, while sadness produced slower walking with longer stride times and reduced cadence. Interestingly, gait variability did not differ significantly across emotional states. These findings demonstrate that IMUs can capture emotion specific gait changes previously documented with motion capture, supporting their feasibility for use in natural and clinical contexts. This work advances understanding of how emotions shape gait and highlights the potential of wearable technology for unobtrusive emotion and mobility research.

Indexed as

EmotionsGaitWalkingAdultBiomechanical PhenomenaFemaleHumansMaleSpatio-Temporal AnalysisWearable Electronic DevicesYoung Adultemotiongaitgait variabilityinertial measurement unitsspatiotemporal parameterswearable sensors

Identifiers

PMID41095043
PMCPMC12526802

What OpenQuestion holds

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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.