The team are the first to investigate the use of acoustic emissions (AE) to detect interactions between knee joint tissues during weight bearing movement during a sit-stand-sit movement.
Similar principles are widely utilised in non-destructive testing and condition monitoring of engineering structures for early detection of damage and material defects.
In this study the team aim to evaluate AE as a biomarker for osteoarthritis of the knee, validating its use for future clinical trials in which the ability of new therapeutics to improve or reduce deterioration of joint conditions in knee osteoarthritis will be assessed.
The study will also assess the ability of AE to provide better discrimination between patient subgroups for inclusion in clinical trials, and to inform stratified medicine approaches for optimising the use of such treatments in clinical practice.
AE sensors are attached to knee surfaces, using defined anatomical positions, to record short bursts of acoustic energy generated by stress upon, and friction between, joint components during weight-bearing movement. An electrogoniometer is also attached to enable each acquired AE waveform to be linked to knee angle.
Data is processed and analysed based on the sound waveforms during different movement phases.
Published results demonstrate clearly that AE can distinguish not only between healthy and osteoarthritic knees, but also between knees in different age groups and differences in joint condition, providing a scientific rationale for investigating the performance of AE as a potential biomarker.