Abstract: K. Kręcisz, D. Bkaczkowicz (2018)

Background and Objective
Vibroarthrography (VAG) is a method developed for sensitive and objective assessment of articular function. Although the VAG method is still in development, it shows high accuracy, sensitivity and specificity when comparing results obtained from controls and the non-specific, knee-related disorder group. However, the multiclass classification remains practically unknown. Therefore the aim of this study was to extend the VAG method classification to 5 classes, according to different disorders of the patellofemoral joint.

Methods
We assessed 121 knees of patients (95 knees with grade I-III chondromalacia patellae, 26 with osteoarthritis) and 66 knees from 33 healthy controls. The vibroarthrographic signals were collected during knee flexion/extension motion using an acceleration sensor. The genetic search algorithm was chosen to select the most relevant features of the VAG signal for classification. Four different algorithms were used for classification of selected features: logistic regression with automatic attribute selection (SimpleLogistic in Weka), multilayer perceptron with sigmoid activation function (MultilayerPerceptron), John Platt's sequential minimal optimization algorithm implementation of support vector classifier (SMO) and random forest tree (RandomForest). The generalization error of classification algorithms was evaluated by stratified 10-fold cross-validation.

Results
We obtained levels of accuracy and AUC metrics over 90%, more than 93% sensitivity and more than 84% specificity for the logistic regression-based method (SimpleLogistic) for a 2-class classification. For the 5-class method, we obtained 69% and 90% accuracy and AUC respectively, and sensitivity and specificity over 91% and 69%.

Conclusions
The results of this study confirm the high usefulness of quantitative analysis of VAG signals based on classification techniques into normal and pathological knees and as a promising tool in classifying signals of various knee joint disorders and their stages.

Please note: The abstracts of the bibliography database may underly other copyrights.

Ihr Browser versucht gerade eine Seite aus dem sogenannten Internet auszudrucken. Das Internet ist ein weltweites Netzwerk von Computern, das den Menschen ganz neue Möglichkeiten der Kommunikation bietet.

Da Politiker im Regelfall von neuen Dingen nichts verstehen, halten wir es für notwendig, sie davor zu schützen. Dies ist im beidseitigen Interesse, da unnötige Angstzustände bei Ihnen verhindert werden, ebenso wie es uns vor profilierungs- und machtsüchtigen Politikern schützt.

Sollten Sie der Meinung sein, dass Sie diese Internetseite dennoch sehen sollten, so können Sie jederzeit durch normalen Gebrauch eines Internetbrowsers darauf zugreifen. Dazu sind aber minimale Computerkenntnisse erforderlich. Sollten Sie diese nicht haben, vergessen Sie einfach dieses Internet und lassen uns in Ruhe.

Die Umgehung dieser Ausdrucksperre ist nach §95a UrhG verboten.

Mehr Informationen unter www.politiker-stopp.de.

Analysis and multiclass classification of pathological knee joints using vibroarthrographic signals