% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@PHDTHESIS{Kolditz:788761,
author = {Kolditz, Melanie},
othercontributors = {Abel, Dirk and Albracht, Kirsten},
title = {{R}oboterassistierte {R}ehabilitation und
{M}uskelaufbautraining},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
reportid = {RWTH-2020-04750},
pages = {1 Online-Ressource (xiii, 148 Seiten) : Illustrationen,
Diagramme},
year = {2020},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University; Dissertation, Rheinisch-Westfälische Technische
Hochschule Aachen, 2020},
abstract = {Mobility is an integral component for an independent life
even in an advanced age. Regular exercise is crucial for
both prevention and rehabilitation of disorders, which can
result in impaired mobility. Robot-assisted systems can help
to provide patients in neurorehabilitation sufficient
independent exercise time and support people in muscular
strength training in avoiding bad postures, which might
result in damages to the musculoskeletal system. The focus
of this work is on the use of industrial robots for
neurorehabilitation of the upper extremity and for
neuromuscular strength training of the lower extremity. A
simulative method, that compares the maximum permissible
axes loads with the loads expected in the application is
used to evaluate and select a suitable robot. The simulation
uses a rigid body model of the robot. A system based on a
KUKA LBR IV is used to improve a robotic system for
neurorehabilitation. The resulting system allows patients to
exercise a previously recorded movement with the robot,
independently. The system continuously evaluates the
patient's arm posture and detects compensatory movements.
This detection is used to assess the patient's current
situation with the measured forces at the end effector and
to react appropriately. A system based on a KUKA KR270
industrial robot has been developed for neuromuscular
strength training, which can be used for both isokinematic
and isotonic exercise along arbitrary individual
trajectories. In two experiments on a dynamic and static leg
press, the position and orientation of the foot plate was
identified as a manipulated variable in order to control
loads on the musculoskeletal system. With motion detection
as well as a rigid body model of the leg, the measured force
at the end effector can be used to determine the joint
loadings during exercise. This is the basis for a management
of loadings in neuromuscular strength training, which is now
possible with the robot-assisted training system developed
in this thesis.},
cin = {416610},
ddc = {620},
cid = {$I:(DE-82)416610_20140620$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2020-04750},
url = {https://publications.rwth-aachen.de/record/788761},
}
guest ::