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General Orthopaedics

Vibroarthography of the Knee Joint: A Comprehensive Gui-Based Analysis of Soft Tissue Damage

International Society for Technology in Arthroplasty (ISTA) 2012 Annual Congress



Abstract

Introduction

The low-cost, no-harm conditions associated with vibroarthography, the study of listening to the vibrations and sound patterns of interaction at the human joints, has made this method a promising tool for diagnosing joint pathologies. This current study focuses on the knee joint and aims to synchronize computational models with vibroarthographic signals via a comprehensive graphical user interface (GUI) to find correlations between kinematics, vibration signals, and joint pathologies. This GUI is the first of its kind to synchronize computational models with vibroarthographic signals and gives researchers a new advantage of analyzing kinematics, vibration signals, and pathologies simultaneously in an easy-to-use software environment.

Methods

The GUI (Figure 1) has the option to view live or previously captured fluoroscopic videos, the corresponding computational model, and/or the pre- or post-processed vibration signals. Having more than one signal axes available allows for comparison of different filtering techniques to the same signal, or comparison of signals coming from different sensor placements (ex: medial vs. lateral femoral condyle). Using computational models derived using fluoroscopic data synchronized with the vibration signals, the areas of contact between articulating surfaces can be mapped for the in vivo signal (figure 2). This new method gives the opportunity to find correlations between the different sensor signals and contact maps with the diagnosis and cartilage degeneration map, provided by a surgeon, during arthroscopy or TKA implantation (figure 3).

Results

Using previously captured data and newly acquired data for subjects from research studies, several different knee pathologies have been analyzed. The signals were listened to audibly after being processed to add a qualitative side. Sounds coming from knees with pathologies revealed noticeable differences compared to the healthy subjects, and the quantitative analysis further supported our hypothesis (>96% accuracy classification patella arthritic subjects vs. healthy).

Discussion

Ideally, transitioning towards real-time kinematic tracking with signal acquisition allows for diagnostic screening tools of the knee joint that will provide feedback of cartilage damage maps as well as potential meniscal or ligament injuries. The method used in this study is multi-faceted in that it allows the subject to perform various daily weight or non-weight bearing activities at his/her own speed which makes it easier to use than if the subject had to be in a very controlled environment.