Evidence map›Paper›PMID 42197975›Full record

SynthesisSensors (Basel, Switzerland)2026

Electronic Systems for Monitoring Pediatric Gait Biomechanical Parameters: A Systematic Review of Embedded Technologies and Human-Machine Interfaces.

Omar Freddy Chamorro-Atalaya

Abstract readSystematic Review
In one paragraph

Synthesis 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

1 author.

Omar Freddy Chamorro-AtalayaFacultad de Ingeniería Mecánica y Electrónica, Universidad Nacional Tecnológica de Lima Sur, Lima 15834, Peru.ORCID 0000-0002-7076-6728

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic systems are increasingly used to support pediatric gait assessment by enabling objective measurement of biomechanical parameters beyond traditional laboratory settings. However, although technological development has expanded in adult populations, the extent to which embedded technologies and human-machine interaction (HMI) modalities have been integrated into pediatric monitoring systems remains unclear. This systematic review synthesizes evidence published between 2015 and 2025 on electronic systems applied to pediatric gait biomechanics. The review followed PRISMA guidelines, was registered in PROSPERO (CRD420251230372), and adopted a descriptive synthesis approach. A total of 2619 records were identified, and after eligibility assessment and methodological quality appraisal using CASP, 34 studies were included in the final synthesis. The studies were examined according to system type, interaction characteristics, and biomechanical outcomes. The findings indicate a predominance of wearable architectures and inertial sensing technologies in the literature on electronic systems for pediatric gait monitoring. However, HMI modalities were rarely described, and most systems functioned primarily as passive data acquisition tools. Biomechanical outcomes focused mainly on motion-derived parameters, whereas region-specific plantar-load distribution was infrequently assessed, and no studies reported the use of force-sensitive resistors for zonal pressure monitoring. These findings suggest that future advances may depend on integrative approaches that combine multimodal sensing, interaction mechanisms, and functional load characterization.

Indexed as

GaitMan-Machine SystemsBiomechanical PhenomenaChildHumansMonitoring, PhysiologicWearable Electronic Deviceselectronic monitoring systemsembedded technologiesinertial measurement unitspediatric gait biomechanicsplantar pressurewearable sensors

Identifiers

PMID42197975
PMCPMC13210630

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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.