Literature DB >> 34757899

A Feasibility Study on Tribological Origins of Knee Acoustic Emissions.

Sevda Gharehbaghi, Hyeon Ki Jeong, Mohsen Safaei, Omer T Inan.   

Abstract

OBJECTIVE: Considering the knee as a fluid-lubricated system, articulating surfaces undergo different lubrication modes and generate joint acoustic emissions (JAEs). The goal of this study is to compare knee biomechanical signals against synchronously recorded joint sounds and assess the hypothesis that JAEs are attributed to tribological origins.
METHODS: JAE, electromyography, ground reaction force signals, and motion capture markers were synchronously recorded from ten healthy subjects while performing two-leg and one-leg squat exercises. The biomechanical signals were processed to calculate a tribological parameter, lubrication coefficient, and JAEs were divided into short windows and processed to extract 64-time-frequency features. The lubrication coefficients and JAE features of two-leg squats were used to label the windows and train a classifier that discriminates the knee lubrication modes only based on JAE features.
RESULTS: The classifier was used to predict the label of one-leg squat JAE windows and it achieved a high test-accuracy of 84%. The Pearson correlation coefficient between the estimated friction coefficient and predicted JAE scores was 0.83 ± 0.08. Furthermore, the lubrication coefficient threshold, separating two lubrication modes, decreased by half from two-leg to one-leg squats. This result was consistent with tribological changes in the knee load as it was inversely doubled in one-leg squats. SIGNIFICANCE: This study supports the potential use of JAEs as a quantitative biomarker to extract tribological information. Since arthritis and similar disease impact the roughness of the joint cartilage, the use of JAEs could have broad implications for studying joint frictions and monitoring joint structural changes with wearable devices.

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Year:  2022        PMID: 34757899      PMCID: PMC9132215          DOI: 10.1109/TBME.2021.3127030

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.756


  32 in total

1.  Measurement and interpretation of synovial fluid viscosities.

Authors:  C H BARNETT
Journal:  Ann Rheum Dis       Date:  1958-06       Impact factor: 19.103

2.  A biomechanical comparison of the traditional squat, powerlifting squat, and box squat.

Authors:  Paul A Swinton; Ray Lloyd; Justin W L Keogh; Ioannis Agouris; Arthur D Stewart
Journal:  J Strength Cond Res       Date:  2012-07       Impact factor: 3.775

Review 3.  Bio-tribology.

Authors:  Duncan Dowson
Journal:  Faraday Discuss       Date:  2012       Impact factor: 4.008

4.  Quantifying the Consistency of Wearable Knee Acoustical Emission Measurements During Complex Motions.

Authors:  Hakan Toreyin; Hyeon Ki Jeong; Sinan Hersek; Caitlin N Teague; Omer T Inan
Journal:  IEEE J Biomed Health Inform       Date:  2016-06-10       Impact factor: 5.772

5.  Estimating Knee Joint Load Using Acoustic Emissions During Ambulation.

Authors:  Keaton L Scherpereel; Nicholas B Bolus; Hyeon Ki Jeong; Omer T Inan; Aaron J Young
Journal:  Ann Biomed Eng       Date:  2020-10-09       Impact factor: 3.934

6.  Quantifying the Effects of Increasing Mechanical Stress on Knee Acoustical Emissions Using Unsupervised Graph Mining.

Authors:  Hyeon-Ki Jeong; Maziyar Baran Pouyan; Daniel C Whittingslow; Venu Ganti; Omer T Inan
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-03       Impact factor: 3.802

7.  Quantifying Signal Quality for Joint Acoustic Emissions Using Graph-Based Spectral Embedding.

Authors:  Kristine L Richardson; Sevda Gharehbaghi; Goktug C Ozmen; Mohsen M Safaei; Omer T Inan
Journal:  IEEE Sens J       Date:  2021-04-07       Impact factor: 4.325

8.  Acoustical Emission Analysis by Unsupervised Graph Mining: A Novel Biomarker of Knee Health Status.

Authors:  Sinan Hersek; Maziyar Baran Pouyan; Caitlin N Teague; Michael N Sawka; Mindy L Millard-Stafford; Geza F Kogler; Paul Wolkoff; Omer T Inan
Journal:  IEEE Trans Biomed Eng       Date:  2017-08-29       Impact factor: 4.538

9.  Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions.

Authors:  Rangaraj M Rangayyan; Y F Wu
Journal:  Med Biol Eng Comput       Date:  2007-10-25       Impact factor: 2.602

10.  CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks.

Authors:  Claudio Pizzolato; David G Lloyd; Massimo Sartori; Elena Ceseracciu; Thor F Besier; Benjamin J Fregly; Monica Reggiani
Journal:  J Biomech       Date:  2015-10-19       Impact factor: 2.712

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