An Artificial Neural Network classification approach for use the ultrasound in physiotherapy.
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.
Işik
Hakan
H
Department of Electronic and Computer Education, Selcuk University, Konya, Turkey. hisik@selcuk.edu.tr
Arslan
Sema
S
D050154:Adiposity; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000465:Algorithms; D001499:Bayes Theorem; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012680:Sensitivity and Specificity; D012867:Skin; D018608:Ultrasonography, Doppler / Q000295:instrumentation / Q000379:methods*; D014652:Vascular Diseases / Q000000981:diagnostic imaging*