Ultrasound intensity and treatment time fuzzy logic control system for low cost effective ultrasound therapy devices

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Abstract

Therapeutic ultrasound is an emerging field with many medical applications. High intensity focused ultrasound provides the ability to localize the deposition of acoustic energy within the body, which can cause tissue necrosis and hemostasis. The ultrasound applied in therapy is usually ranged from 1MHz to 1000MHz. Even the least vibration of 1MHz would be as keen as a sharp knife to cut off steels, if we reinforce its amplitude. However, the output of the ultrasound used in treating people must be decreased substantially. A specific increase in temperature is necessary to achieve a temperaturemediated therapeutic impact by ultrasound in rehabilitation. On a large scale ultrasound intensity determines the temperature level on the tissue. High intensity causes a marked mechanical peak loading of the tissue. This may even lead to tissue damage. The extreme pressure differences developing as a consequence of exposure to ultrasound may cause cavitations in the tissues. Opinions in the literature on the duration of treatment also vary. The duration of treatment depends on the size of the body area to be treated. Lehmann fixes the maximum duration of treatment at 15 minutes. This refers to a treated area of 75-100 cm 2 which he considers the maximum area that can reasonably be treated. New medical applications have required advances in biomedical equipment design and advances in numerical and experimental studies of the interaction of sound with biological tissues and fluids. In this study a fuzzy logic control system will be explained which was developed in order to obtain optimum ultrasound intensity and determine optimum treatment time during ultrasound therapy (UT). This system also increases patient safety and comfort during UT. © 2006 Springer.

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APA

Yardimci, A., & Celik, O. (2006). Ultrasound intensity and treatment time fuzzy logic control system for low cost effective ultrasound therapy devices. Advances in Soft Computing, 33, 797–807. https://doi.org/10.1007/3-540-31182-3_75

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