基于模糊的体系测定膝关节与骨关节炎的严重级

Fuzzy-Based System for Determining the Severity Level of Knee Osteoarthritis

I.J. Intelligent Systems and Applications, 2012, 9, 46-53

Published Online August 2012 in MECS (/) DOI: 10.5815/ijisa.2012.09.06

Fuzzy-Based System for Determining the Severity Level of Knee Osteoarthritis

Emuoyibofarhe O. Justice

Dept. of Computer Science and Engineering, Ladoke Akintola University of Technology, Ogbomosho, Nigeria

eojustice@ , +2348033850075

Taiwo K.F

Dept. of Compurt Science, Federal College of Education (Tech.), Gombe, Nigeria

victory4kemi@

Abstract— the task of medical diagnosis, unlike other diagnostic processes is more complex because a lot of vagueness, linguistic uncertainty, subjectivity, measurement imprecision, natural diversity are all prominently present in medical diagnosis. Osteoarthritis (OA) of the knee is a major public health issue causing chronic disability and reduction in quality of life; it is reported to be associated with a significant decline in function and causes a higher rate of disability than any other chronic condition. Osteoarthritis (OA) exacts a cost in terms of pain, limited mobility, and decreased function among a wide range of individuals. With improvement in science and technology, intelligent computing has been used to assist in enhancing qualitative services.

This paper reports the development of a fuzzy-based system to determine the level of severity of knee osteoarthritis, given some input conditions. The system was implemented and simulated using MATLAB Fuzzy Logic Toolbox. The results are entrusting and promising based on the flexibility and case of adaptability.

Index Terms— Fuzzy-System, Knee, Osteoarthritis, Severity Level I.

Introduction

lot of vagueness, linguistic uncertainty, hesitation, measurement imprecision, natural diversity are all prominently present in medical diagnosis. With improvement in science and technology, intelligent computing has been used assisting in enhancing qualitative services, thereby reducing the mortality rate and also alleviating the economic burden placed on the society through lost working time as well as social and medical costs due to one ailment or the other of which osteoarthritis is not an exception. Fuzzy logic (a paradigm of artificial intelligence), provides a mathematical tool for dealing with the uncertainty and imprecision typical of human reasoning has been used in assisting the medical personal in making decision [2]. Fuzzy can also be described as a tool of artificial intelligence based on the observation that people make decisions based on imprecise and non-numerical information [3]. Using fuzzy logic in medical diagnosis is a promising technique that can easily capture the required medical knowledge and come up with sound diagnosis decisions. Practically, an expert physician tends usually to specify his experience in rather fuzzy terms, which is more natural to him than trying to cast his knowledge in rigid rules having abrupt premises [4]. Osteoarthritis (OA) is a type of arthritis that is caused by the breakdown and eventual loss of cartilage for one or more joints. It is the most common form of arthritis and the major cause of activity limitation and physical disability in older people [5]. It is characterized clinically by pain, enlargement and deformity of the joints and limitation of motion. Among the most commonly affected sites in osteoarthritis, the knee is the major source of reported disability and loss of function [6]. Some other words used to describe osteoarthritis, including osteoarthrosis‘, arthrosis‘ and degenerative joint disease‘. Osteoarthritis of the knee is a very common form of osteoarthritis. Other joints which are often affected include joints in the hands, the spine, the hip joint and the big toe joint. Osteoarthritis (OA) of the knee is a major public health issue causing chronic disability and reduction in quality of life, there is no cure nor an objective or accurate method for measurement of the structural severity in general clinical practice [7], hence the need to develop a system

Numerous techniques have been applied over the past decades to solve medical problems: expert systems, artificial neural networks, linear programming and database systems are a few samples of the approaches used, however, fuzzy logic seems to have an edge over these techniques because it provides a simple way to arrive at a definite conclusion based on vague, ambiguous, imprecise, noisy, or missing input information and allows intermediate values to be defined between conventional evaluations like true/false, yes/no, high/low, hence a more human-like way of thinking in the programming of computers [1]. The task of medical diagnosis, unlike other diagnostic processes is made more complex because a