Evidence map›Paper›PMID 41228819›Full record

ArticleSensors (Basel, Switzerland)2025

A Reliability Study of Small, Portable, Easy-to-Use, and IMU-Based Sensors for Gait Assessment.

Maciej Tomasz Kochman, Aleksandra Kielar, Marta Kasprzak, Wojciech Kasperek, Martin Dutko, Adam Vellender, Grzegorz Przysada, Mariusz Drużbicki

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Maciej Tomasz KochmanDepartment of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzeszów, Tadeusza Rejtana Avenue 16C, 35-310 Rzeszów, Poland.ORCID 0000-0003-0174-7133
Aleksandra KielarFaculty of Medicine, College Medicum, University of Rzeszów, Tadeusza Rejtana Avenue 16C, 35-310 Rzeszów, Poland.ORCID 0009-0005-3884-780X
Marta KasprzakDepartment of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzeszów, Tadeusza Rejtana Avenue 16C, 35-310 Rzeszów, Poland.ORCID 0009-0000-2789-9843
Wojciech KasperekDepartment of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzeszów, Tadeusza Rejtana Avenue 16C, 35-310 Rzeszów, Poland.ORCID 0000-0003-1981-8454
Martin DutkoRockfield Software Limited, Swansea SA1 8AS, UK.
Adam VellenderDepartment of Mathematics, Aberystwyth University, Aberystwyth SY23 3BZ, UK.
Grzegorz PrzysadaFaculty of Medicine, College Medicum, University of Rzeszów, Tadeusza Rejtana Avenue 16C, 35-310 Rzeszów, Poland.
Mariusz DrużbickiDepartment of Clinical Physiotherapy in Musculoskeletal Disorders, Faculty of Health Sciences and Psychology, Institute of Physiotherapy, College Medicum, University of Rzeszów, Tadeusza Rejtana Avenue 16C, 35-310 Rzeszów, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The standard motion analysis systems are limited to laboratory settings; therefore, an individual's gait may not be realistic, as it is removed from the day-to-day environment in which people ambulate. The modern world and advanced technologies have driven portable, affordable, and wearable sensors for real-world gait assessment that can be used outside the laboratory and during day-to-day activities. Wearable sensors offer a promising solution; however, despite that, the reliability of many wearable systems, especially under unsupervised and real-world-like conditions, remains insufficiently validated. This study aimed to establish intra- and inter-rater reliability of the inertial sensors as a tool used in gait analysis in a quasi-real-world environment. Ninety-eight healthy participants (52% females) aged 19-33 years took part in this reliability study. The research procedures included two separate measurements of gait analysis at participants' preferred walking speed, conducted by two raters assessing selected spatiotemporal parameters. The reliability was calculated using intraclass correlation coefficients (ICC), and the bias was assessed using the Bland-Altman method. The analysis of intraclass correlation coefficients (ICC) revealed excellent, or near-excellent, reliability for walking speed, cadence, and stride length between raters (ICC = 0.932-0.941, 0.950-0.957, and 0.916-0.938, respectively) and between measurements (ICC = 0.916-0.928, 0.934-0.938, and 0.888-0.906, respectively). Bland-Altman plots confirmed minimal systematic bias for both inter- and intra-rater assessments, with differences in walking speed below 0.038 km/h, cadence below 0.283 steps/min, and stride length below 0.827 cm. The examined sensors are reliable tools for walking speed, cadence, and stride length in a quasi-real-world environment gait assessment. Future studies should include gait analysis involving random path and direction changes, turns, uneven or slippery surfaces, and natural environments. Additionally, research should consider individuals ambulating with various walking aids, or those with unilateral disorders, such as stroke.

Indexed as

GaitGait AnalysisWearable Electronic DevicesAdultFemaleHumansMaleReproducibility of ResultsWalkingYoung Adultgaitreliabilitysensorswalkingwearable devices

Identifiers

PMID41228819
PMCPMC12608381

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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.