Evidence map›Paper›PMID 31097924›Full record

ArticleIEEE sensors journal2018

Using Knee Acoustical Emissions for Sensing Joint Health in Patients with Juvenile Idiopathic Arthritis: A Pilot Study.

Beren Semiz, Sinan Hersek, Daniel C Whittingslow, Lori Ponder, Sampath Prahalad, Omer T Inan

Abstract read
In one paragraph

Article in IEEE sensors journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. A Feasibility Study on Tribological Origins of Knee Acoustic Emissions.IEEE transactions on bio-medical engineering · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
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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

6 authors.

Beren Semiz *School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332 USA.
Sinan Hersek *School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332 USA.
Daniel C Whittingslow *Emory University School of Medicine and Georgia Institute of Technology Coulter Department of Biomedical Engineering under MD/PhD program.
Lori PonderDepartment of Pediatrics, Emory University School of Medicine, and Children's Healthcare of Atlanta, Atlanta, GA.
Sampath PrahaladDepartments of Pediatrics and Human Genetics, Emory University School of Medicine, and Children's Healthcare of Atlanta, Atlanta, GA.
Omer T InanSchool of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332 USA.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM008169 · NIGMS · EMORY UNIVERSITY · PI GROSS, ROBERT E · 1987 to 2021
$20.3M
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 EB023808NIGMS NIH HHS T32 GM008169
6 · The paper itself

Abstract

In this paper, we present a pilot study evaluating novel methods for assessing joint health in patients with Juvenile Idiopathic Arthritis (JIA) using wearable acoustical emission measurements from the knees. Measurements were taken from four control subjects with no known knee injuries, and from four subjects with JIA, before and after treatment. Time and frequency domain features were extracted from the acoustical emission signals and used to compute a knee audio score. The score was used to separate out the two groups of subjects based solely on the sounds their joints produce. It was created using a soft classifier based on gradient boosting trees. The knee audio scores ranged from 0-1 with 0 being a healthy knee and 1 being an involved joint with arthritis. Leave-one-subject-out cross-validation (LOSO-CV) was used to validate the algorithm. The average of the right and left knee audio scores was 0.085±0.099 and 0.89±0.012 for the control group and group with JIA, respectively (p<0.05). The average knee audio score for the subjects with JIA decreased from 0.89±0.012 to 0.25±0.20 following successful treatment (p<0.05). The knee audio score metric successfully distinguished between the control subjects and subjects with JIA. The scores calculated before and after treatment accurately reflected the observed clinical course of the subjects with JIA. After successful treatment, the subjects with JIA were classified as healthy by the algorithm. Knee acoustical emissions provide a novel and cost-effective method for monitoring JIA, and can be used as an objective guide for assessing treatment efficacy.

Indexed as

acousticsknee joint healthWearable technologies

Identifiers

PMID31097924
PMCPMC6512979

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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.