Evidence map›Paper›PMID 29674288›Full record

ArticleGait & posture2018

A flexible wearable sensor for knee flexion assessment during gait.

Enrica Papi, Yen Nee Bo, Alison H McGregor

Abstract readValidation Study
In one paragraph

Article in Gait & posture, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Wearable Loop Sensors for Knee Flexion Monitoring: Dynamic Measurements on Human Subjects.IEEE open journal of engineering in medicine and biology · 2024
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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

3 authors.

Enrica PapiDepartment of Surgery and Cancer, Imperial College London, London, UK; Department of Bioengineering, Imperial College London, London, UK. Electronic address: e.papi@imperial.ac.uk.
Yen Nee BoDepartment of Surgery and Cancer, Imperial College London, London, UK.
Alison H McGregorDepartment of Surgery and Cancer, Imperial College London, London, UK.

Funding

Wellcome TrustWellcome Trust 088844/Z/09/Z
6 · The paper itself

Abstract

backgroundGait analysis plays an important role in the diagnosis and management of patients with movement disorders but it is usually performed within a laboratory. Recently interest has shifted towards the possibility of conducting gait assessments in everyday environments thus facilitating long-term monitoring. This is possible by using wearable technologies rather than laboratory based equipment. RESEARCH QUESTION: This study aims to validate a novel wearable sensor system's ability to measure peak knee sagittal angles during gait.

methodsThe proposed system comprises a flexible conductive polymer unit interfaced with a wireless acquisition node attached over the knee on a pair of leggings. Sixteen healthy volunteers participated to two gait assessments on separate occasions. Data was simultaneously collected from the novel sensor and a gold standard 10 camera motion capture system. The relationship between sensor signal and reference knee flexion angles was defined for each subject to allow the transformation of sensor voltage outputs to angular measures (degrees). The knee peak flexion angle from the sensor and reference system were compared by means of root mean square error (RMSE), absolute error, Bland-Altman plots and intra-class correlation coefficients (ICCs) to assess test-retest reliability.

resultsComparisons of knee peak flexion angles calculated from the sensor and gold standard yielded an absolute error of 0.35(±2.9°) and RMSE of 1.2(±0.4)°. Good agreement was found between the two systems with the majority of data lying within the limits of agreement. The sensor demonstrated high test-retest reliability (ICCs>0.8). SIGNIFICANCE: These results show the ability of the sensor to monitor knee peak sagittal angles with small margins of error and in agreement with the gold standard system. The sensor has potential to be used in clinical settings as a discreet, unobtrusive wearable device allowing for long-term gait analysis.

Indexed as

Wearable Electronic DevicesAdultBiomechanical PhenomenaFemaleGaitHealthy VolunteersHumansKneeMaleReproducibility of ResultsGait analysisKnee kinematicsKnee monitoringWalkingWearable technology

Identifiers

PMID29674288
PMCPMC5980996

What OpenQuestion holds

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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.