Evidence map›Paper›PMID 41556288›Full record

ArticleMuscle & nerve2026

Stance and Gait Analysis of Apollo Astronauts on the Moon.

Faye Y Chiou-Tan, Conrad Li, Jason P Caffrey, Millard Reschke, Timothy R Macaulay

Abstract read
In one paragraph

Article in Muscle & nerve, 2026. 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

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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

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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

5 authors.

Faye Y Chiou-TanH. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas, USA.ORCID https://orcid.org/0009-0004-2172-1816
Conrad LiMedical School, Texas A&M University, School of Engineering Medicine, Houston, Texas, USA.
Jason P CaffreyH. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas, USA.
Millard ReschkeH. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas, USA.
Timothy R MacaulayNeuroscience Laboratory, NASA Johnson Space Center, Houston, Texas, USA.

Funding

Lee Family/Hae Ahm (Sea Rock) Faculty Innovation and Service Award
6 · The paper itself

Abstract

INTRODUCTION/

aimAs humans return to the Moon, safe efficient ambulation and fall prevention on the lunar surface are key concerns. The analysis of gait from archived Apollo mission video footage is now possible with pose estimation video analysis software. Thus, this study aims to retrospectively quantify parameters of Apollo astronauts' stance and gait on the Moon.

methodsPublicly available National Aeronautics and Space Administration (NASA) footage of astronauts ambulating on the Lunar surface was examined using body pose analysis software. Goniometric lower limb joint/torso angles and width of base of stance and gait were derived. Gait cycle stance phase, swing phase, double support time, and estimated speed of gait were all computed.

resultsLunar stance was characterized by 13.3 ± 3.6 SD to 14.3 ± 3.9 SD inch base of stance (based on a 6.5 or 7.0 in. shoe width, respectively), 39.3° ± 9.0° hip flexion, 42.2° ± 14.8° knee flexion, and 17.0° ± 7.5° ankle dorsiflexion. Upper torso anterior tilt was 16.4° ± 8.8°. Lunar gait demonstrated 14.0 ± 2.8 SD to 15.1 ± 2.9 SD base of gait, 0.42 ± 0.16 m/s speed of gait, and 15.4 ± 3.3 in. step length with 40% double support time. Stance phase was 69% and swing phase was 31% of the gait cycle. DISCUSSION: Decreased speed of gait with wide base, short steps, and increased double support time was seen in astronaut gait patterns. This pattern is adopted on Earth to increase stability and prevent falls.

Indexed as

AstronautsGaitGait AnalysisMoonPostureAdultBiomechanical PhenomenaFemaleHumansMaleRetrospective Studiesbody pose analysisgait kinematicslunar ambulationspace travel

Identifiers

PMID41556288
PMCPMC13047954

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.