Knee acoustic emission characteristics of the healthy and the patients with osteoarthritis using piezoelectric sensor

Dagyeong Choi, Soonjae Ahn, Jeseong Ryu, Mitsuo Nagao, Youngho Kim

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Osteoarthritis (OA) is one of the most common causes of disability in elderly individuals. Although X-rays, MRIs, and arthroscopy are widely used to examine OA, they do not provide dynamic information on activity-based joint integrity. In this study, acoustic emission (AE) in healthy individuals and OA patients was determined using piezoelectric sensors. Twenty normal subjects and fourteen OA patients were asked to perform weight-bearing (stand-to-sit) and non-weight-bearing (extension to flexion) exercises for 4 s each. Sensors were attached to the medial and lateral epicondyles of the tibia and the front of the patella. An AE event was defined as the threshold crossing based on AE signals. The results indicated that OA and healthy groups exhibited signals at a frequency range corresponding to approximately 100 Hz-10 kHz and less than 1 kHz, respectively. The OA group exhibited an amplitude of AE signals and a number of AE events that exceeded those of the healthy group (p < 0.05). AE signals from lesions exhibited a higher dB value and a larger number of AE events than those at other locations. However, most patients exhibited significant increases in AE signal characteristics at the front of the patella. The results of this study can be helpful in the early diagnosis or easy monitoring of knee OA in daily lives.

Original languageEnglish
Pages (from-to)1629-1641
Number of pages13
JournalSensors and Materials
Volume30
Issue number8
DOIs
StatePublished - 2018
Externally publishedYes

Keywords

  • Acoustic emission
  • Osteoarthritis
  • Piezoelectric sensor

Fingerprint

Dive into the research topics of 'Knee acoustic emission characteristics of the healthy and the patients with osteoarthritis using piezoelectric sensor'. Together they form a unique fingerprint.

Cite this