scholarly journals Quantitative assessment of upper limb motor function in Multiple Sclerosis using an instrumented Action Research Arm Test

2014 ◽  
Vol 11 (1) ◽  
pp. 67 ◽  
Author(s):  
Ilaria Carpinella ◽  
Davide Cattaneo ◽  
Maurizio Ferrarin
2018 ◽  
Vol 26 ◽  
pp. 647-653 ◽  
Author(s):  
Kristina Daunoraviciene ◽  
Jurgita Ziziene ◽  
Julius Griskevicius ◽  
Jolanta Pauk ◽  
Agne Ovcinikova ◽  
...  

2019 ◽  
Vol 10 ◽  
Author(s):  
Charmayne M. L. Hughes ◽  
Moges Baye ◽  
Chloe Gordon-Murer ◽  
Alexander Louie ◽  
Selena Sun ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yali Liu ◽  
Qiuzhi Song ◽  
Chong Li ◽  
Xinyu Guan ◽  
Linhong Ji

With the popularization of rehabilitation robots, it is necessary to develop quantitative motor function assessment methods for patients with a stroke. To make the assessment equipment easier to use in clinics and combine the assessment methods with the rehabilitation training process, this paper proposes an anthropomorphic rehabilitation robot based on the basic movement patterns of the upper limb, point-to-point reaching and circle drawing movement. This paper analyzes patients’ movement characteristics in aspects of movement range, movement accuracy, and movement smoothness and the output force characteristics by involving 8 patients. Besides, a quantitative assessment method is also proposed based on multivariate fitting methods. It can be concluded that the area of the real trajectory and movement accuracy during circle drawing movement as well as the ratio of force along the sagittal axis in backward point-to-point movement are the unique parameters that are different remarkably between stroke patients and healthy subjects. The fitting function has a high goodness of fit with the Fugl-Meyer scores for the upper limb (R2=0.91, p=0.015), which demonstrates that the fitting function can be used to assess patients’ upper limb movement function. The indicators are recorded during training movement, and the fitting function can calculate the scores immediately, which makes the functional assessment quantitative and timely. Combining the training process and assessment, the quantitative assessment method will farther expand the application of rehabilitation robots.


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