Abstract
In medical practice, there is no appropriate widely-used application of a system based on fuzzy logic for identifying the lower limb movement type or type of walking. The object of our study was to determine characteristics of the cyclogram to identify the gait behavior by using a fuzzy logic system. The set of data for setting and testing the fuzzy logic system was measured on 10 volunteers recruited from healthy students of the Czech Technical University in Prague. The human walking speed was defined by the treadmill speed, and the inclination angle of the surface was defined by the treadmill and terrain slope. The input to the fuzzy expert system is based on the following variables: the area and the inclination angle of the cyclogram. The output variables from the fuzzy expert system are: the inclination angle of the surface, and the walking speed. We also tested the method with input based on the angle of inclination of the surface and the walking speed, and with the output based on the area and the inclination angle of the cyclogram. We found that identifying the type of terrain and walking speed on the basis of an evaluation of the cyclogram could be sufficiently accurate and suitable if we need to know the approximate type of walking and the approximate inclination angle of the surface. According to the method described here, the cyclograms could provide information about human walking, and we can infer the walking speed and the angle of inclination of the terrain.
Highlights
In medical practice, there is no widely-used application of a system based on fuzzy logic for identifying lower limb movement type or type of walking
We assume that the type of terrain and the walking speed strongly affect the characteristics of the cyclogram
Walking is described by the cyclogram, and the cyclogram is used to identify the type of terrain and the walking speed
Summary
There is no widely-used application of a system based on fuzzy logic for identifying lower limb movement type or type of walking. Time and phase diagrams of gait behavior have been used to analyze gait with the application of artificial intelligence methods [4,5,6,7], but the findings have not subsequently been applied in medical practice. For a study of gait, we have used methods based on an analysis of gait angles using cyclograms ( called angle-angle diagrams or cyclokinograms) and artificial intelligence [13] to identify gait behavior. Applications of cyclograms in conjunction with fuzzy logic can offer a wide range of medical applications, but this approach has not yet been studied or applied in practice. Our paper investigates the application of the fuzzy rule based expert system (FRBES) to the identification of human gait behavior
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