Evidence map›Paper›PMID 42884382›Full record

ArticleSensors (Basel, Switzerland)2026

Assessment of Task-Specific Gait and Balance Deficits in Chronic Low Back Pain Using Multi-Sensor Inertial Measurement Units.

Yen-Chang Chien, Lik-Kang Koo, Chia-Wei Chang, Chien-Cheng Chen, Szu-Fu Chen, Fu-Cheng Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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

6 authors.

Yen-Chang ChienDepartment of Physical Medicine and Rehabilitation, Cheng Hsin General Hospital, Taipei 112, Taiwan.ORCID 0009-0006-0851-8877
Lik-Kang KooDepartment of Physical Medicine and Rehabilitation, Cheng Hsin General Hospital, Taipei 112, Taiwan.
Chia-Wei ChangDepartment of Mechanical Engineering, National Taiwan University, Taipei 106, Taiwan.
Chien-Cheng ChenDepartment of Physical Medicine and Rehabilitation, Cheng Hsin General Hospital, Taipei 112, Taiwan.
Szu-Fu ChenDepartment of Physical Medicine and Rehabilitation, Cheng Hsin General Hospital, Taipei 112, Taiwan.ORCID 0000-0002-8398-883X
Fu-Cheng WangDepartment of Mechanical Engineering, National Taiwan University, Taipei 106, Taiwan.ORCID 0000-0001-5011-7934

Funding

Cheng Hsin General Hospital NDMC-113-112-02, CHGH115-N2Ministry of Science and Technology MOST 111-2221-E-002-190-MY3National Science and Technology Council NSTC 114-2221-E-002-178-MY2
6 · The paper itself

Abstract

Chronic low back pain (cLBP) compromises daily function, but associated balance deficits remain difficult to quantify using traditional scales. We recruited 50 participants with CLBP (age: 65.68 ± 11.84) and 50 age-matched controls (age: 65.26 ± 10.73) wearing multiple inertial measurement units (IMUs) to evaluate kinematics: average absolute angular velocity (Jω) and linear acceleration (Jα) across static (single-leg stance), perturbed (balance board), locomotor (walking, tandem gait), and transitional (five times sit-to-stand) tasks. Group differences were assessed using multivariate analysis of variance and Bonferroni-adjusted univariate tests. During the balance board test, Jω was significantly higher at the chest (p = 0.027) and hip (p = 0.003) in the CLBP group. Conversely, during the sit-to-stand tests, the CLBP group showed significantly lower Jα and Jω (

Indexed as

GaitLow Back PainPostural BalanceAgedBiomechanical PhenomenaFemaleHumansMaleMiddle Agedangular velocitiesbalancechronic low back paingaitinertial measurement unit

Identifiers

PMID42884382
PMCPMC13667449

What OpenQuestion holds

Textmetadata
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.