Modified Constraint-Induced Movement Therapy for Upper Extremity Recovery Post Stroke: What Is the Evidence?

2014 ◽  
Vol 21 (4) ◽  
pp. 319-331 ◽  
Author(s):  
Alana Fleet ◽  
Stephen J. Page ◽  
Marilyn MacKay-Lyons ◽  
Shaun G. Boe
2009 ◽  
Vol 24 (6) ◽  
pp. 929-933
Author(s):  
Taichi KURAYAMA ◽  
Anna WATANABE ◽  
Minami TAKAMOTO ◽  
Nami SHIGETA ◽  
Yuki HASEGAWA ◽  
...  

2021 ◽  
pp. 1-16
Author(s):  
Gitendra Uswatte ◽  
Edward Taub ◽  
Peter Lum ◽  
David Brennan ◽  
Joydip Barman ◽  
...  

Background: Although Constraint-Induced Movement therapy (CIMT) has been deemed efficacious for adults with persistent, mild-to-moderate, post-stroke upper-extremity hemiparesis, CIMT is not available on a widespread clinical basis. Impediments include its cost and travel to multiple therapy appointments. To overcome these barriers, we developed an automated, tele-health form of CIMT. Objective: Determine whether in-home, tele-health CIMT has outcomes as good as in-clinic, face-to-face CIMT in adults ≥1-year post-stroke with mild-to-moderate upper-extremity hemiparesis. Methods: Twenty-four stroke patients with chronic upper-arm extremity hemiparesis were randomly assigned to tele-health CIMT (Tele-AutoCITE) or in-lab CIMT. All received 35 hours of treatment. In the tele-health group, an automated, upper-extremity workstation with built-in sensors and video cameras was set-up in participants’ homes. Internet-based audio-visual and data links permitted supervision of treatment by a trainer in the lab. Results: Ten patients in each group completed treatment. All twenty, on average, showed very large improvements immediately afterwards in everyday use of the more-affected arm (mean change on Motor Activity Log Arm Use scale = 2.5 points, p <  0.001, d’ = 3.1). After one-year, a large improvement from baseline was still present (mean change = 1.8, p <  0.001, d’ = 2). Post-treatment outcomes in the tele-health group were not inferior to those in the in-lab group. Neither were participants’ perceptions of satisfaction with and difficulty of the interventions. Although everyday arm use was similar in the two groups after one-year (mean difference = –0.1, 95%CI = –1.3–1.0), reductions in the precision of the estimates of this parameter due to drop-out over follow-up did not permit ruling out that the tele-health group had an inferior long-term outcome. Conclusions: This proof-of-concept study suggests that Tele-AutoCITE produces immediate benefits that are equivalent to those after in-lab CIMT in stroke survivors with chronic upper-arm extremity hemiparesis. Cost savings possible with this tele-health approach remain to be evaluated.


2012 ◽  
Vol 19 (6) ◽  
pp. 499-513 ◽  
Author(s):  
Amanda McIntyre ◽  
Ricardo Viana ◽  
Shannon Janzen ◽  
Swati Mehta ◽  
Shelialah Pereira ◽  
...  

2013 ◽  
Vol 27 (2) ◽  
pp. 31-38 ◽  
Author(s):  
Marta Sidaway ◽  
Edyta Czernicka ◽  
Arkadiusz Sosnowski

StreszczenieNeuroplastyczność jest zjawiskiem powszechnym w działaniu układu nerwowego, a samoistne i spontaniczne zdrowienie jest normą we wczesnym okresie poudarowym. Zmiany plastyczne leżą u podstaw przywracania funkcji po uszkodzeniu mózgu. Reprezentacje czuciowe i ruchowe pól korowych mogą być modyfikowane przez dopływ bodźców ze środowiska. Odpowiednio dobrane strategie postępowania fizjoterapeutycznego mają wpływ na spontaniczną neuroplastyczność. Przedstawiono podstawowe założenia działań terapeutycznych mających korzystny wpływ, na omawiane zjawisko reorganizacji układu nerwowego oraz uczenia się kontekstualnego, szczególnie w odniesieniu do zagadnienia Terapii Ruchem Wymuszonym Koniecznością. Opisano protokół Tauba dotyczący tej terapii oraz stanowiący jej podwalinę zespół wyuczonego nieużywania. Przybliżono zagadnienie shapingu i praktyki zadaniowej (ćwiczeń zadaniowych). Głównym celem opisywanej terapii jest przywrócenie spontanicznego i automatycznego wykorzystania kończyny niedowładnej w czynnościach dnia codziennego.Na zjawisko plastyczności istotny wpływ mają: wzbogacone środowisko, odległość czasu od zachorowania, liczba powtórzeń zadań ruchowych oraz znajomość wykonywanych czynności co potwierdzają dowody naukowe.Prawidłowo prowadzona terapia pozwala przenieść osiągnięte umiejętności poza ściany kliniki i przyczynia się do funkcjonalnej niezależności pacjentów.


2019 ◽  
Vol 99 (12) ◽  
pp. 1667-1678 ◽  
Author(s):  
Mohammad H Rafiei ◽  
Kristina M Kelly ◽  
Alexandra L Borstad ◽  
Hojjat Adeli ◽  
Lynne V Gauthier

Abstract Background Constraint-induced movement therapy (CI therapy) produces, on average, large and clinically meaningful improvements in the daily use of a more affected upper extremity in individuals with hemiparesis. However, individual responses vary widely. Objective The study objective was to investigate the extent to which individual characteristics before treatment predict improved use of the more affected arm following CI therapy. Design This study was a retrospective analysis of 47 people who had chronic (&gt; 6 months) mild to moderate upper extremity hemiparesis and were consecutively enrolled in 2 CI therapy randomized controlled trials. Methods An enhanced probabilistic neural network model predicted whether individuals showed a low, medium, or high response to CI therapy, as measured with the Motor Activity Log, on the basis of the following baseline assessments: Wolf Motor Function Test, Semmes-Weinstein Monofilament Test of touch threshold, Motor Activity Log, and Montreal Cognitive Assessment. Then, a neural dynamic classification algorithm was applied to improve prognostic accuracy using the most accurate combination obtained in the previous step. Results Motor ability and tactile sense predicted improvement in arm use for daily activities following intensive upper extremity rehabilitation with an accuracy of nearly 100%. Complex patterns of interaction among these predictors were observed. Limitations The fact that this study was a retrospective analysis with a moderate sample size was a limitation. Conclusions Advanced machine learning/classification algorithms produce more accurate personalized predictions of rehabilitation outcomes than commonly used general linear models.


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