Application of EEMD-DFA algorithms and ann classification for detection of knee osteoarthritis using vibroarthrography
Artykuł w czasopiśmie
MNiSW
70
Lista 2024
Status: | |
Autorzy: | Machrowska Anna, Karpiński Robert, Maciejewski Marcin, Jonak Józef, Krakowski Przemysław |
Dyscypliny: | |
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Rok wydania: | 2024 |
Wersja dokumentu: | Drukowana | Elektroniczna |
Język: | angielski |
Numer czasopisma: | 2 |
Wolumen/Tom: | 20 |
Strony: | 90 - 108 |
Scopus® Cytowania: | 3 |
Bazy: | Scopus |
Efekt badań statutowych | NIE |
Finansowanie: | This research was funded by the Scientific Fund of the Lublin University of Technology: FD/IM/052 |
Materiał konferencyjny: | NIE |
Publikacja OA: | TAK |
Licencja: | |
Sposób udostępnienia: | Witryna wydawcy |
Wersja tekstu: | Ostateczna wersja opublikowana |
Czas opublikowania: | W momencie opublikowania |
Data opublikowania w OA: | 30 czerwca 2024 |
Abstrakty: | angielski |
Osteoarthritis is one of the leading causes of disability around the globe. Up to this date there is no definite cure for cartilage lesions. Only fast and accurate diagnosis enables prolonging joint survivor time. Available diagnostic methods have disadvantages such as high price, radiation, need for experienced radiologists or low availability in some regions. The present study evaluates the use of vibroarthorgraphy as a method of cartilage lesion detection. 47 patients with diagnosed cartilage lesions, and 51 healthy control group patients have been enrolled in this study. The cartilage in the study group was evaluated intraoperatively by experienced orthopaedic surgeon. Signal acquisition was performed in open and closed kinematic chain based on 10 knee joint movements from 0-90 degrees. By using EEMD-DFA algorithms, reducing classifier inputs using ANOVA and then classifying using artificial neural networks (ANN), a classification accuracy of almost 93% was achieved. A sensitivity of 0.93 and a specificity of 0.93 with an AUC of 0.942 were obtained for the multilayer perceptron network. These results allow to apply this testing protocol in a clinical setting in the future. |