Evidence map›Paper›PMID 28026745›Full record

ArticleIEEE transactions on bio-medical engineering2017

Wearable Vector Electrical Bioimpedance System to Assess Knee Joint Health.

Sinan Hersek, Hakan Toreyin, Caitlin N Teague, Mindy L Millard-Stafford, Hyeon-Ki Jeong, Miheer M Bavare, Paul Wolkoff, Michael N Sawka, Omer T Inan

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
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  7. A review of bio-impedance devices.Medical & biological engineering & computing · 2023
    Review
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  20. Quantifying the Effects of Increasing Mechanical Stress on Knee Acoustical Emissions Using Unsupervised Graph Mining.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018
    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

9 authors.

Sinan Hersek
Hakan Toreyin
Caitlin N Teague
Mindy L Millard-Stafford
Hyeon-Ki Jeong
Miheer M Bavare
Paul Wolkoff
Michael N Sawka
Omer T Inan

Funding

Wearable lung sounds, fluid, and body temperature monitoring for patients with COVID-19R01EB023808 · NIBIB · GEORGIA INSTITUTE OF TECHNOLOGY · PI INAN, OMER TOLGA · 2016 to 2020
$2.2M
NIBIB NIH HHS R01 EB023808
6 · The paper itself

Abstract

objectiveWe designed and validated a portable electrical bioimpedance (EBI) system to quantify knee joint health.

methodsFive separate experiments were performed to demonstrate the: 1) ability of the EBI system to assess knee injury and recovery; 2) interday variability of knee EBI measurements; 3) sensitivity of the system to small changes in interstitial fluid volume; 4) reducing the error of EBI measurements using acceleration signals; and 5) use of the system with dry electrodes integrated to a wearable knee wrap.

results1) The absolute difference in resistance ( R) and reactance (X) from the left to the right knee was able to distinguish injured and healthy knees (p < 0.05); the absolute difference in R decreased significantly (p < 0.05) in injured subjects following rehabilitation. 2) The average interday variability (standard deviation) of the absolute difference in knee R was 2.5 Ω and for X was 1.2 Ω. 3) Local heating/cooling resulted in a significant decrease/increase in knee R (p < 0.01). 4) The proposed subject position detection algorithm achieved 97.4% leave-one subject out cross-validated accuracy and 98.2% precision in detecting when the subject is in the correct position to take measurements. 5) Linear regression between the knee R and X measured using the wet electrodes and the designed wearable knee wrap were highly correlated ( R

conclusionThis study demonstrates the use of wearable EBI measurements in monitoring knee joint health. SIGNIFICANCE: The proposed wearable system has the potential for assessing knee joint health outside the clinic/lab and help guide rehabilitation.

Indexed as

Biosensing TechniquesConductometryEquipment DesignEquipment Failure AnalysisHumansKnee InjuriesKnee JointPlethysmography, ImpedanceReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID28026745
PMCPMC5509509

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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.