Knee acoustic emission: A potential biomarker for quantitative assessment of joint ageing and degeneration

• Published in: Medical engineering & physics 2011-06, Vol.33 (5), p.534-545
• Main Authors: Shark, L.-K, Chen, H, Goodacre, J
• Format: Article
• Language: English
• Subjects: Acoustic emission; Acoustics; Adult; Aged; Aged, 80 and over; Aging; Biological and medical sciences; Biomarkers; Case-Control Studies; Diseases of the osteoarticular system; Humans; Knee; Knee Joint - pathology; Knee Joint - physiology; Knee Joint - physiopathology; Knee joint ageing and degeneration; Medical sciences; Middle Aged; Miscellaneous. Osteoarticular involvement in other diseases; Movement; Osteoarthritis; Osteoarthritis, Knee - physiopathology; Principal Component Analysis; Radiology; Young Adult
• ISSN: 1350-4533; 1873-4030
• DOI: 10.1016/j.medengphy.2010.12.009

Abstract Based on a single time-point study of 34 healthy and 19 osteoarthritic knees in three different age groups (early, middle and late adulthood), this paper reports the potential of knee acoustic emission as a biomarker to monitor joint ageing and degeneration. Measurements were made of short transient high frequency acoustic emission signals generated by knee joints under stress during repeated sit–stand–sit movements along with joint angle. A statistically significant feature profile was established using a four-phase model of sit–stand–sit movements and two waveform features. The four-phase movement model is derived from joint angle measurement during repeated sit–stand–sit movements, and it consists of the ascending-acceleration and ascending-deceleration phases in the sit-to-stand movement, followed by the descending-acceleration and descending-deceleration phases in the stand-to-sit movement. The two statistically significant waveform features are extracted from AE measurement during repeated sit–stand–sit movements, and they consist of the peak magnitude value and average signal level of each AE burst. In addition to the use of bilateral plots, statistical distributions and 2D colour histograms to visualise the differences and similarities among participants, use of principal component analysis showed not only distinct data clusters corresponding to participating groups, but also an age- and disease-related trajectory progressing from the early adulthood healthy group to the late adulthood healthy group followed by the middle adulthood osteoarthritic group to the late adulthood osteoarthritic group. Furthermore, this trajectory shows increasing areas for each data cluster, with a highly compact cluster for the early adulthood healthy group at one end and a widely spread cluster for the late adulthood osteoarthritic group at the other end. From these results, a strong basis is formed for further development of knee acoustic emission as a convenient and non-invasive biomarker for quantitative assessment of joint ageing and degeneration.