Analysis of Doppler signals of radial artery for diagnosis of rheumatoid arthritis

Abstract

In this study, Doppler signals received from the radial artery of the right hands of the 40 healthy subjects and 40 patients with rheumatoid arthritis were recorded. Some features of these signals were obtained using Subspace-based MUSIC method which is one of the spectral analysis methods, and the diseased cases were distinguished with Artificial Neural Networks classification method. In MUSIC method, 5,10,15,20 and 25 were used as model degrees. Test procedure was carried out after training with Artificial Neural Networks. Classification accuracy after the test results was 88.75% for 5 model degrees, 93.75% for 10 and 25 model degrees, 100% for 15 model degrees and 92.5% for 20 model degrees and all models had an average degree of 93.75% classification accuracy was obtained. The proposed approach has potential to help with the early diagnosis of RA disease for the specialists who study this subject.