Robot therapy for upper limb rehabilitation in multiple sclerosis: A virtual approach and a functional approach

2009 ◽  
Vol 30 ◽  
pp. S28-S29
Author(s):  
I. Carpinella ◽  
D. Cattaneo ◽  
R. Bertoni ◽  
M. Rovaris ◽  
D. Caputo ◽  
...  
2020 ◽  
Vol 38 (4) ◽  
pp. 333-341
Author(s):  
Marco Tramontano ◽  
Giovanni Morone ◽  
Sara De Angelis ◽  
Laura Casagrande Conti ◽  
Giovanni Galeoto ◽  
...  

Background: Sensor-based technological therapy devices may be good candidates for neuromotor rehabilitation of people with Multiple Sclerosis (MS), especially for treating upper extremities function limitations. The sensor-based device rehabilitation is characterized by interactive therapy games with audio-visual feedback that allows training the movement of shoulders, elbows, and wrist, measuring the strength and the active range of motion of upper limb, registering data in an electronic database to quantitatively monitoring measures and therapy progress. Objective: This study aimed to investigate the effects of sensor-based motor rehabilitation in add-on to the conventional neurorehabilitation, on increasing the upper limb functions of patients with MS. Methods: Thirty patients were enrolled in the study and randomly assigned to the experimental group and the control group. The training consisting of twelve sessions of upper limb training was compared with twelve sessions of upper limb sensory-motor training, without robotic support. Both rehabilitation programs were performed for 40 minutes three times a week, for 4 weeks, in addition to conventional therapy. All patients were evaluated at the baseline (T0) and after 4 weeks of training (T1). Results: The within-subject analysis showed a statistically significant improvement in both groups, in the Modified Barthel Index and in the Rivermead Mobility Index scores and a significant improvement in Multiple Sclerosis Quality of Life-54 in the experimental. The analysis of effectiveness revealed that, compared with baseline (T0), the improvement percentage in all clinical scale scores was greater in the experimental group than the control group. Conclusions: Proposed training provides an intensive and functional-oriented rehabilitation that objectively evaluates achieved progress through exercises. Therefore, it can represent a good complementary strategy for hand rehabilitation in MS patients.


2020 ◽  
Vol 44 (2) ◽  
pp. 142-150
Author(s):  
Wioletta Pawlukowska ◽  
Natalia Dobrowolska ◽  
Aleksandra Szylinska ◽  
Dorota Koziarska ◽  
Agnieszka Meller ◽  
...  

Objective To assess the influence of cognitive therapy, in combination with cognitive software, on manual dexterity in individuals with multiple sclerosis (MS).Methods The Nine-Hole Peg Test (NHPT) was used to establish the eligibility of individuals with MS for testing and to assess their upper limb performance. In addition to standard upper limb rehabilitation, 20 participants received RehaCom-based visual-motor therapy, administered three times a week in 20-minute routines.Results A significant relationship was found between the use of manual therapy that utilized the cognitive function platform and the improvement of the non-dominant hand (p=0.037). Compared to controls, the experimental group scored higher on the NHPT, when using the dominant hand (p=0.007). All members of the experimental group, aged ≤60 years, needed considerably less time to do the NHPT with the dominant hand (p=0.008).Conclusion Application of manual therapy using the cognitive function platform improves performance of the hand. However, further research is needed to analyze the correlation between cognitive function and motor performance in patients with MS.


2016 ◽  
Vol 30 (8) ◽  
pp. 773-793 ◽  
Author(s):  
Ilse Lamers ◽  
Anneleen Maris ◽  
Deborah Severijns ◽  
Wouter Dielkens ◽  
Sander Geurts ◽  
...  

2013 ◽  
Vol 56 ◽  
pp. e358
Author(s):  
P. Gallien ◽  
B. Nicolas ◽  
A. Durufle-Tapin ◽  
S. Petrilli ◽  
K. Autret ◽  
...  

ROBOT ◽  
2011 ◽  
Vol 33 (3) ◽  
pp. 307-313 ◽  
Author(s):  
Baoguo XU ◽  
Si PENG ◽  
Aiguo SONG

ROBOT ◽  
2012 ◽  
Vol 34 (5) ◽  
pp. 539 ◽  
Author(s):  
Lizheng PAN ◽  
Aiguo SONG ◽  
Guozheng XU ◽  
Huijun LI ◽  
Baoguo XU

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