Discovery of acoustic emission based biomarker for quantitative assessment of knee joint ageing and degeneration

Based on the study of 34 healthy and 19 osteoarthritic knees in three different age groups (early, middle and late adulthood), this thesis reports the discovery of the potential of knee acoustic emission (AE) as a biomarker for quantitative assessment of joint ageing and degeneration. Signal processing and statistical analysis were conducted on the joint angle signals acquired using electronic goniometers attached to the lateral side of the legs during repeated sit- stand-sit movements. A four-phase movement model derived from joint angle measurement is proposed for statistical analysis, and it consists of the ascending- acceleration and ascending-deceleration phases in the sit-to- stand movement, followed by the descending-acceleration and descending-deceleration phases in the stand-to-sit movement. Through the quantitative assessment of joint angle signals based on the four-phase model established, statistical differences of different knee conditions related to age and degeneration were discovered based on cycle-by- cycle variations and movement symmetry. For AE burst signals acquired from piezo-electric sensors attached to the knee joints during repeated sit-stand-sit movements, the statistical analysis started from the quantity of AE events in the proposed four movement phases and extended to waveform features extracted from AE signals. While the quantity of AE events was found to follow certain statistical trends related to age and degeneration in each movement phase, detail statistical analysis of AE waveform features yielded the peak amplitude value and average signal level of each AE burst as two most significant features. An image based knee AE feature profile is presented based on 2D colour histograms formed by the peak amplitude value and average signal level in four movement phases. It provides not only a visual trend related to knee age and degeneration, but also enables visual assessment of th

Acoustic Monitoring of Joint Health

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

Discovering Associations between Acoustic Emission and Magnetic Resonance Imaging Biomarkers from 10 Osteoarthritic Knees

Objective: Acoustic emission (AE) sensed from knee joints during weight-bearing movements greatly increases with joint deterioration, but the relationship between AE patterns and specific anatomical damage, as seen for example in magnetic resonance imaging (MRI), is unknown. This knowledge is essential to validate AE biomarkers for the evaluation of knee joints, and forms the objective of this exploratory work to associate knee AE and MRI. Methods: A novel processing framework is proposed to enable direct correlation between static 3D MRI of knees and their dynamic 1D AE during sit-stand-sit movements. It comprises a method to estimate articular cartilage thickness according to joint angle from knee MRI, and a method to derive statistically representative waveform features according to joint angle from movement and load-dependent knee AE. Results: In 10 subjects diagnosed with knee osteoarthritis, age 55~79 years and body mass index 25~35 kg/m2, a strong inverse relationship between knee AE and cartilage thickness in the medial tibiofemoral compartment around the fully standing position was observed. Knees with thinner articular cartilage generated more AE with higher amplitude, greater energy, longer duration, and higher frequencies, in agreement with the assumption of more intense articulation friction under full body weight. Conclusion: AE provides promising quantitative biomarkers in knee joint disease. Significance: These findings provide impetus for the further development of AE as a low-cost non-invasive biomarker modality to improve the management of knee joint disease

Advances in Sensors and Sensing for Technical Condition Assessment and NDT

The adequate assessment of key apparatus conditions is a hot topic in all branches of industry. Various online and offline diagnostic methods are widely applied to provide early detections of any abnormality in exploitation. Furthermore, different sensors may also be applied to capture selected physical quantities that may be used to indicate the type of potential fault. The essential steps of the signal analysis regarding the technical condition assessment process may be listed as: signal measurement (using relevant sensors), processing, modelling, and classification. In the Special Issue entitled “Advances in Sensors and Sensing for Technical Condition Assessment and NDT”, we present the latest research in various areas of technology

A Systematic Review and Meta-Analysis of the Incidence of Injury in Professional Female Soccer

The epidemiology of injury in male professional football is well documented and has been used as a basis to monitor injury trends and implement injury prevention strategies. There are no systematic reviews that have investigated injury incidence in women’s professional football. Therefore, the extent of injury burden in women’s professional football remains unknown. PURPOSE: The primary aim of this study was to calculate an overall incidence rate of injury in senior female professional soccer. The secondary aims were to provide an incidence rate for training and match play. METHODS: PubMed, Discover, EBSCO, Embase and ScienceDirect electronic databases were searched from inception to September 2018. Two reviewers independently assessed study quality using the Strengthening the Reporting of Observational Studies in Epidemiology statement using a 22-item STROBE checklist. Seven prospective studies (n=1137 professional players) were combined in a pooled analysis of injury incidence using a mixed effects model. Heterogeneity was evaluated using the Cochrane Q statistic and I2. RESULTS: The epidemiological incidence proportion over one season was 0.62 (95% CI 0.59 - 0.64). Mean total incidence of injury was 3.15 (95% CI 1.54 - 4.75) injuries per 1000 hours. The mean incidence of injury during match play was 10.72 (95% CI 9.11 - 12.33) and during training was 2.21 (95% CI 0.96 - 3.45). Data analysis found a significant level of heterogeneity (total Incidence, X2 = 16.57 P < 0.05; I2 = 63.8%) and during subsequent sub group analyses in those studies reviewed (match incidence, X2 = 76.4 (d.f. = 7), P <0.05; I2 = 90.8%, training incidence, X2 = 16.97 (d.f. = 7), P < 0.05; I2 = 58.8%). Appraisal of the study methodologies revealed inconsistency in the use of injury terminology, data collection procedures and calculation of exposure by researchers. Such inconsistencies likely contribute to the large variance in the incidence and prevalence of injury reported. CONCLUSIONS: The estimated risk of sustaining at least one injury over one football season is 62%. Continued reporting of heterogeneous results in population samples limits meaningful comparison of studies. Standardising the criteria used to attribute injury and activity coupled with more accurate methods of calculating exposure will overcome such limitations