Evidence map›Paper›PMID 39716173›Full record

Observational studyBMC musculoskeletal disorders2024

Effect of wearable robot Bot Fit's hip joint-centered assist torque and voice coach on walking.

Jang-Hoon Shin, Naeun Byeon, Heeju Yu, Dokwan Lee, Hwang-Jae Lee, Wan-Hee Lee

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in BMC musculoskeletal disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07277166 (The Effect of Mobile Robot Assisted Gait Training on Gait Performance in Chronic Patients With Impaired Gait Function After Burn Injury), which is not on this 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.

NCT07277166 narecruitingnot on this mapstarted 2025, after this paper: background citation

The Effect of Mobile Robot Assisted Gait Training on Gait Performance in Chronic Patients With Impaired Gait Function After Burn Injury : Pilot Study

TypeinterventionalSponsorHangang Sacred Heart HospitalRan2025 to 2026Enrolled20ConditionsBurns, Gait Dysfunction, Robot TrainingArmswearable robot training
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

6 authors.

Jang-Hoon ShinIndustry-Academy Cooperation Foundation, Sahmyook University, 01795, Seoul, Republic of Korea.
Naeun ByeonDepartment of Physical Therapy, Applied Physical Therapy Lab, College of Future Convergence, Sahmyook University, Seoul, 01795, Republic of Korea.
Heeju YuDepartment of Physical Therapy, Applied Physical Therapy Lab, College of Future Convergence, Sahmyook University, Seoul, 01795, Republic of Korea.
Dokwan LeeBot Fit T/F, New Business T/F, Samsung Electronics, Suwon, 16677, Republic of Korea.
Hwang-Jae LeeBot Fit T/F, New Business T/F, Samsung Electronics, Suwon, 16677, Republic of Korea. hwangjae.lee@samsung.com.
Wan-Hee LeeDepartment of Physical Therapy, Applied Physical Therapy Lab, College of Future Convergence, Sahmyook University, Seoul, 01795, Republic of Korea. whlee@syu.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe main key to the 4th industrial era is robots, and wearable robots are incorporated into human healthcare. Samsung Electronics' Bot Fit is a hip joint-centered assistive robot that can induce walking posture and energetic walking exercises.

methodsThis study is a cross-section study. Fifty-eight subjects consisting of older and younger adults participated. The straight walking test was conducted under the conditions of bare body, wearing the wearable robot Bot Fit assist mode, and applying voice coach. Spatio-temporal gait parameters were analyzed and the statistical significance level was set at 0.05.

resultsWhen assist mode and voice coach were applied, pelvic movement in 3 axes, stride length, and walking speed compared to the bare body increased. In young adults, stride length difference decreased in assist mode 1 and voice coach 1 compared to the bare body.

conclusionBot Fit's assist mode and voice coach method positively influence walking efficiency, posture, stride length, and speed, though potential interaction effects between these interventions should be considered. Personalized, real-time adjustments show promise for optimizing walking exercises, warranting further investigation into their long-term and population-specific effects.

trial registrationClinical Research Information Service, KCT0007974. Registered 12/07/2022.

Indexed as

Exoskeleton DeviceHip JointRoboticsWalkingWearable Electronic DevicesAdultAgedAged, 80 and overBiomechanical PhenomenaCase-Control StudiesCross-Sectional StudiesExerciseFemaleHealthy VolunteersHumansMaleGaitMovementPelvisPostureRobotics

Identifiers

PMID39716173
PMCPMC11665193

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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.