Acoustic monitoring of joint health

Spain, Lucy ORCID: https://orcid.org/0000-0002-6442-6778 and Cheneler, David (2020) Acoustic monitoring of joint health. In: Płaczek, Dr. Bartłomiej, (ed.) Data acquisition: recent advances and applications in biomedical engineering. IntechOpen, London, UK, pp. 31-50.

Preview

PDF - Published Version Available under License CC BY Download (732kB) | Preview

Abstract

The joints of the human body, especially the knees, are continually exposed to varying loads as a person goes about their day. These loads may contribute to damage to tissues including cartilage and the development of degenerative medical conditions such as osteoarthritis (OA). The most commonly used method currently for classifying the severity of knee OA is the Kellgren and Lawrence system, whereby a grade (a KL score) from 0 to 4 is determined based on the radiographic evidence. However, radiography cannot directly depict cartilage damage, and there is low inter-observer precision with this method. As such, there has been a significant activity to find non-invasive and radiation-free methods to quantify OA, in order to facilitate the diagnosis and the appropriate course of medical action and to validate the development of therapies in a research or clinical setting. A number of different teams have noted that variation in knee joint sounds during different loading conditions may be indicative of structural changes within the knee potentially linked to OA. Here we will review the use of acoustic methods, such as acoustic Emission (AE) and vibroarthrography (VAG), developed for the monitoring of knee OA, with a focus on the issues surrounding data collection and analysis.

Item Type:	Book Section
Publisher:	IntechOpen
ISBN:	9781839680373
Departments:	Institute of Health > Medical Sciences
Additional Information:	Chapter 3 within book. This chapter is distributed under the terms of the Creative Commons Attribution License.
Depositing User:	Christian Stretton
Date Deposited:	29 Jun 2020 12:38
Last Modified:	11 Jan 2024 16:31
URI:	https://insight.cumbria.ac.uk/id/eprint/5596

Downloads