Literature DB >> 20703780

An Artificial Neural Network classification approach for use the ultrasound in physiotherapy.

Hakan Işik1, Sema Arslan.   

Abstract

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.

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Year:  2010        PMID: 20703780     DOI: 10.1007/s10916-009-9410-6

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  11 in total

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  2 in total

1.  Comparing methods for determining motor-hand lateralization based on fTCD signals.

Authors:  Walter H L Pinaya; Francisco J Fraga; Salo S Haratz; Philip J A Dean; Adriana B Conforto; Edson Bor-Seng-Shu; Manoel J Teixeira; João R Sato
Journal:  J Med Syst       Date:  2015-01-27       Impact factor: 4.460

2.  Investigating the Effectiveness of Wavelet Approximations in Resizing Images for Ultrasound Image Classification.

Authors:  Umar Manzoor; Samia Nefti; Milella Ferdinando
Journal:  J Med Syst       Date:  2016-09-01       Impact factor: 4.460

  2 in total

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