Evidence map›Paper›PMID 42197996›Full record

ArticleSensors (Basel, Switzerland)2026

Self-Powered Triboelectric Insole for Gait Asymmetry and Plantar Pressure Signatures in Rehabilitation Patients: A Cross-Sectional Study.

Perizat Kanabekova, Adeliya Anash, Pedro Morouco, Bekzhan Pirmakhanov, Gulnur Kalimuldina

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

5 authors.

Perizat KanabekovaDepartment of Mechanical and Aerospace Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana 010000, Kazakhstan.ORCID 0000-0001-5753-4271
Adeliya AnashDepartment of Mechanical and Aerospace Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana 010000, Kazakhstan.
Pedro MoroucoNational Program for Physical Activity Promotion, Directorate-General of Health, 1049-005 Lisbon, Portugal.ORCID 0000-0002-5956-9790
Bekzhan PirmakhanovMirai Technovation Ltd., Astana 010000, Kazakhstan.ORCID 0000-0002-1512-8141
Gulnur KalimuldinaDepartment of Mechanical and Aerospace Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana 010000, Kazakhstan.ORCID 0000-0001-9185-3217

Funding

Nazarbayev University 111024CRP2010
6 · The paper itself

Abstract

(1) Background: Gait analysis technologies have advanced; however, traditional systems like optical motion capture are lab-bound and costly, limiting rehabilitation monitoring. This cross-sectional study evaluates self-powered triboelectric nanogenerator (TENG) insoles combined with IMU sensors to assess gait asymmetry, plantar pressure signatures, age effects and injury history in rehabilitation patients, aiming to enable portable, battery-free phenotyping. (2) Methods: Fifty-three patients (22 females, 31 males; age, 29 ± 26 years) from Astana clinics with trauma histories (e.g., spine, ankle, fractures) and 10 healthy references underwent a 2 min walk test (2MWT). TENG insoles captured plantar loading; ankle/knee IMUs measured spatiotemporal parameters (cadence, asymmetry). The data were normalized; the analyses used an ANOVA and correlations (Python 3.14.3). (3) Results: The TENG sensors showed force/frequency linearity (up to 10 V at 20 N). The cadence averaged 101 ± 10 steps/min, declining with age (r = -0.31,

Indexed as

FootFoot OrthosesGaitAdultBiomechanical PhenomenaCross-Sectional StudiesFemaleHumansMalePressureYoung Adultbiomechanical analysisgait analysislower limbself-powered sensorstriboelectric nanogenerator

Identifiers

PMID42197996
PMCPMC13210678

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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.