Osteoarthritis (OA) is a growing societal burden, due to the ageing population. Less invasive, less damaging, and cheaper methods for diagnosis are needed, and sound technology is an emerging tool in this field. The aim of the current research was to: 1) investigate the potential of visual scalogram analysis of Acoustic Emission (AE) frequencies within the human audible range (20–20000 Hz) to diagnose knee OA, 2) correlate the qualitative visual scalogram analysis of the AE with OA symptoms, and 3) to do this based on information gathered during gait.INTRODUCTION
AIMS
Osteoarthritis (OA) is a growing societal burden, due to the ageing population. Less invasive, less damaging, and cheaper methods for diagnosis are needed, and sound technology is an emerging tool in this field. Some studies investigate ultrasound signals, while others look at acoustic signals in the audible range. The aim of the current research was to: 1) investigate the potential of visual scalogram analysis of Acoustic Emission (AE) frequencies within the human audible range (20–20000 Hz) to diagnose knee OA, 2) correlate the qualitative visual scalogram analysis of the AE with OA symptoms, and 3) to do this based on information gathered during gait.INTRODUCTION
AIMS
