Non-invasive Assessment of Cartilage Damage of the Human Knee using Acoustic Emission Monitoring: a Pilot Cadaver Study

Liudmila Khokhlova, Dimitrios-Sokratis Komaris, Nikolaos Davarinos, Karuppiah Mahalingam, Brendan O'Flynn, Salvatore Tedesco

Research output: Contribution to journalArticlepeer-review


Objective: Knee osteoarthritis is currently one of the top causes of disability in older population, a rate that will only increase in the future due to an aging population and the prevalence of obesity. However, objective assessment of treatment outcomes and remote evaluation are still in need of further development. Acoustic emission (AE) monitoring in knee diagnostics has been successfully adopted in the past; however, a wide discrepancy among the adopted AE techniques and analyses exists. This pilot study determined the most suitable metrics to differentiate progressive cartilage damage and the optimal frequency range and placement of AE sensors. Methods: Knee AEs were recorded in the 100-450 kHz and 15-200kH frequency ranges from a cadaver specimen in knee flexion/extension. Four stages of artificially inflicted cartilage damage and two sensor positions were investigated. Results: AE events in the lower frequency range and the following parameters provided better distinction between intact and damaged knee: hit amplitude, signal strength, and absolute energy. The medial condyle area of the knee was less prone to artefacts and unsystematic noise. Multiple reopenings of the knee compartment in the process of introducing the damage negatively affected the quality of the measurements. Conclusion: Results may improve AE recording techniques in future cadaveric and clinical studies. Significance: This was the first study to evaluate progressive cartilage damage using AEs in a cadaver specimen. The findings of this study encourage further investigation of joint AE monitoring techniques.
Original languageEnglish
Pages (from-to)2741-2751
Number of pages11
Journal IEEE Transactions on Biomedical Engineering
Issue number9
Early online date30 Mar 2023
Publication statusPublished - 1 Sept 2023

Bibliographical note

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  • Knee
  • Monitoring
  • Recording
  • Sensor phenomena and characterization
  • Sensors
  • Sociology
  • Statistics
  • acoustic emission
  • joint sound
  • knee health
  • osteoarthritis
  • thinning of the articular cartilage


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