Medical diagnosis of rheumatoid arthritis disease from right and left hand Ulnar artery Doppler signals using adaptive network based fuzzy inference system (ANFIS) and MUSIC method Ali Osman Özkan a , Sadık Kara b , Ali Salli c , Mehmet Emin Sakarya d , Salih Günes ß e,⇑ a Selcuk University, Vocational College of Technical Sciences, 42003 Konya, Turkey b Fatih University, Institute of Biomedical Engineering, 34500 Istanbul, Turkey c Selcuk University, Meram Faculty of Medicine, Dept. of Physical Med. and Rehabilitation, Konya, Turkey d Selcuk University, Meram Faculty of Medicine, Dept. of Radiology, Konya, Turkey e Selcuk University, Dept. of Electrical and Electronics Eng., 42035 Konya, Turkey article info Article history: Received 14 May 2010 Received in revised form 21 September 2010 Accepted 4 October 2010 Keywords: Rheumatoid arthritis disease Ulnar artery MUSIC method Adaptive network based fuzzy inference system (ANFIS) Doppler ultrasound abstract Rheumatoid arthritis (RA) is a multi-systemic autoimmune disease that leads to substantial morbidity and mortality. In this paper, as spectral analysis methods of Multiple Signal Classification (MUSIC) method is used in order to extract the significant features from the right and left hand Ulnar artery Dopp- ler signals for the diagnosis of RA disease. The MUSIC method has been used as subspace method. To extract features from Doppler signals obtained from the right and left hand Ulnar arterial the MUSIC method model degrees of 5, 10, 15, 20, and 25 were used. Then, an adaptive network based fuzzy infer- ence system (ANFIS) was applied to features extracted from the right and left hand Ulnar artery Doppler signals for classifying RA disease. The methods are not new, but the study has a novelty in that the appli- cation area of these methods is new. In the hybrid model, the combination of MUSIC and ANFIS yielded classification accuracies of 95% (for a model degree of 20) using the right hand Ulnar artery and classifi- cation accuracies of 91.25% (for a model degree of 10) using left hand Ulnar artery Doppler signals in the diagnosis of RA disease. The proposed approach has potential to help with the early diagnosis of RA dis- ease for the specialists who study this subject. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Rheumatoid arthritis (RA) is observed in all races worldwide with varying frequency. Genetic factors play an important role and likely account for about 50% of disease susceptibility [1]. RA is a chronic disease with symmetrical polyarticular involvement and systemic symptoms, such as fatigue and low level fever [2]. RA is an autoimmune disease that causes chronic inflammation in the joints. RA can also cause inflammation of the tissue around the joints, as well as in other organs in the body. Autoimmune dis- eases are illnesses that occur when the body’s tissues are mistak- enly attacked by their own immune system [3]. RA is a systemic chronic inflammatory disorder that mainly affects diarthrodial joints. It is characterized by inflammatory activity of synovium leading to the destruction of bone and joint cartilage along with periarticular structures like tendons and ligaments. It is the most common form of inflammatory arthritis and the world prevalence of RA is approximately 0.3–1.2% in a female/male ratio of 2.5/1. It is most common in patients aged 40–70 years old and its incidence increases with age [4–6]. The Ulnar artery is the main blood vessel of the medial section of the forearm. It arises from the brachial artery and terminates in the superficial palmar arch, which joins with the superficial branch of the radial artery. It is palpable on the anterior and medial section of the wrist [7]. RA disease activity and its therapeutic response is predomi- nantly measured using clinical assessments and laboratory tests for serum markers of inflammation, such as C reactive protein (CRP) or erythrocyte sedimentation rate (ESR). Tenderness and swollen joint counts are essential for physical examinations and evaluating disease activity. They also comprise the Disease Activity Score 28 (DAS 28), which was developed for evaluating disease activity in RA. However, clinical evaluation of joint pain and swell- ing has not been sufficiently reliable [8]. Direct radiography can be used for evaluating established erosions, but gives us little infor- mation on synovial inflammation and early erosions [9]. However, color Doppler ultrasound (CDU) displays blood flow in the tissues and can be a marker of the inflammatory response. Thus, the 0965-9978/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.advengsoft.2010.10.001 ⇑ Corresponding author. E-mail address: sgunes@selcuk.edu.tr (S. Günes ß). Advances in Engineering Software 41 (2010) 1295–1301 Contents lists available at ScienceDirect Advances in Engineering Software journal homepage: www.elsevier.com/locate/advengsoft