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Statements

Subject Item
n2:RIV%2F68407700%3A21460%2F14%3A00221623%21RIV15-MSM-21460___
rdf:type
skos:Concept n14:Vysledek
rdfs:seeAlso
http://link.springer.com/article/10.2478/s11536-013-0322-y
dcterms:description
Quantification of upper extremity movement is a common objective in both research and clinical practice. Currently, methods based on angle-angle diagrams, also called cyclograms, seem to be promising. Nevertheless, compared to the study of lower limbs, the concept of angle-angle diagrams has not been systematically used to study upper limb movements during walking. The paper describes two examples of new methods based on angle-angle diagrams for application in rehabilitation and assistive robotics. The cyclograms represent information about the relationship between the angles and their changes over time. We used cyclograms as patterns for learning artificial neural networks and predicting the movement of upper-limb. Together with artificial intelligence, cyclograms offer wide scope of application in prosthesis control systems. Using bilateral cyclogram, the information about the relationship between the right and left arm joint angles is used to evaluate the symmetry of movements. The method based on the orientation of the bilateral cyclogram can be used as an additional method for determining the symmetry of movements of the upper limbs or exo-prosthesis. Quantification of upper extremity movement is a common objective in both research and clinical practice. Currently, methods based on angle-angle diagrams, also called cyclograms, seem to be promising. Nevertheless, compared to the study of lower limbs, the concept of angle-angle diagrams has not been systematically used to study upper limb movements during walking. The paper describes two examples of new methods based on angle-angle diagrams for application in rehabilitation and assistive robotics. The cyclograms represent information about the relationship between the angles and their changes over time. We used cyclograms as patterns for learning artificial neural networks and predicting the movement of upper-limb. Together with artificial intelligence, cyclograms offer wide scope of application in prosthesis control systems. Using bilateral cyclogram, the information about the relationship between the right and left arm joint angles is used to evaluate the symmetry of movements. The method based on the orientation of the bilateral cyclogram can be used as an additional method for determining the symmetry of movements of the upper limbs or exo-prosthesis.
dcterms:title
Analysis and prediction of upper extremity movements by cyclograms Analysis and prediction of upper extremity movements by cyclograms
skos:prefLabel
Analysis and prediction of upper extremity movements by cyclograms Analysis and prediction of upper extremity movements by cyclograms
skos:notation
RIV/68407700:21460/14:00221623!RIV15-MSM-21460___
n3:aktivita
n19:S
n3:aktivity
S
n3:cisloPeriodika
6
n3:dodaniDat
n6:2015
n3:domaciTvurceVysledku
n5:7826583 n5:3896919 Socha, Vladimír
n3:druhVysledku
n18:J
n3:duvernostUdaju
n10:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
2597
n3:idVysledku
RIV/68407700:21460/14:00221623
n3:jazykVysledku
n16:eng
n3:klicovaSlova
Angle-angle diagram; Artificial intelligence; Asymmetry; Human gait; Upper limb
n3:klicoveSlovo
n7:Upper%20limb n7:Artificial%20intelligence n7:Human%20gait n7:Asymmetry n7:Angle-angle%20diagram
n3:kodStatuVydavatele
AT - Rakouská republika
n3:kontrolniKodProRIV
[6AECE7EA76C7]
n3:nazevZdroje
Central European Journal of Medicine
n3:obor
n4:EI
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:rokUplatneniVysledku
n6:2014
n3:svazekPeriodika
9
n3:tvurceVysledku
Socha, Vladimír Kutílek, Patrik Hána, Karel
n3:wos
000340672300014
s:issn
1895-1058
s:numberOfPages
7
n8:doi
10.2478/s11536-013-0322-y
n15:organizacniJednotka
21460