The longitudinal assessment of joint health is a long-standing issue in the management of musculoskeletal injuries. The acoustic emissions (AEs) produced by joint articulation could serve as a biomarker for joint health assessment, but their use has been limited by a lack of mechanistic understanding of their creation. In this paper, we investigate that mechanism using an injury model in human lower-limb cadavers, and relate AEs to joint kinematics. Using our custom joint sound recording system, we recorded the AEs from nine cadaver legs in four stages: at baseline, after a sham surgery, after a meniscus tear, and post-meniscectomy. We compare the resulting AEs using their b-values. We then compare joint anatomy/kinematics to the AEs using the X-ray reconstruction of moving morphology (XROMM) technique. After the meniscus tear the number and amplitude of the AE peaks greatly increased from baseline and sham (b-value = 1.33 ± 0.15; p < 0.05). The XROMM analysis showed a close correlation between the minimal inter-joint distances (0.251 ± 0.082 cm during extension, 0.265 ± .003 during flexion, at 145°) and a large increase in the AEs. This work provides key insight into the nature of joint AEs, and details a novel technique and analysis for recording and interpreting these biosignals.
Keywords: Cadaver model; Diagnostic; Musculoskeletal assessment; Predictive; Prognostic markers; Wearable sensing; XROMM.