Department of Electronic and Computer Education, Selcuk University, Konya, Turkey.
J Med Syst. 2011 Dec;35(6):1333-41. doi: 10.1007/s10916-009-9410-6. Epub 2010 Jan 6.
In this study, a classification to be used in physiotherapy was realized by means of Artificial Neural Network (ANN). The aim of the classification was to determine the treatment length and appropriate ultrasound value for the age of physiotherapy patients, the area on which ultrasound will be applied, the fat rate in tissue and related factors. For this purpose, the patient information obtained from Selçuk University, Meram School of Medicine Hospital, Physiotherapy Department was used. In order to identify the appropriate ultrasound value and treatment length for the patient, the ultrasound therapy device realized with ANN was placed together in an embedded system. The results obtained by means of the designed and realized embedded system were compared with data gathered from an expert. As a result, the data obtained from the designed system were found out to be in line with the existing data.
在这项研究中,通过人工神经网络(ANN)实现了一种用于物理治疗的分类。分类的目的是确定物理治疗患者的治疗长度和适当的超声值、将应用超声的区域、组织中的脂肪率以及相关因素。为此,使用了从塞尔丘克大学梅拉姆医学院理疗系获得的患者信息。为了为患者确定适当的超声值和治疗长度,将通过 ANN 实现的超声治疗设备一起放置在嵌入式系统中。通过设计和实现的嵌入式系统获得的结果与从专家那里收集的数据进行了比较。结果,发现设计系统获得的数据与现有数据相符。