Impact of the Upper Limb Physiotherapy on Behavioral and Brain Adaptations in Post-Stroke Patients

Author:

Kuwahara Wataru,Miyawaki Yu,Kaneko Fuminari, , ,

Abstract

Many stroke patients suffer from motor impairments due to paralysis, and consequently, motor paralysis of upper limbs seems to be particularly prone to residual impairment compared to that of lower limbs. Although ‘learned non-use’ that by managing reasonably well using only the unaffected upper limb in their actions, the patients can achieve their desired behavior, and these success experiences strengthen this pattern of behavior can be interpreted as a post-stroke adaptation, physiotherapy may lead to poor recovery of motor impairment. This review article discusses the impact of upper limb physiotherapy after stroke on behavioral/brain adaptations. Our previous studies demonstrated that patients with severe post-stroke sensorimotor impairments in a chronic phase might have abnormal functional connectivity. To prevent such adaptation after stroke, upper limb physiotherapy is important. In rehabilitation practices, hyper-adaptation has been often observed in not only behavioral but also brain changes. Although several studies are reporting clinical efficacy in patients with moderate to mild paralysis, there might be no effective treatment for patients with severe motor paralysis. To overcome these serious problems, we have developed a novel approach, kinesthetic illusion induced by visual stimulation (KINVIS) therapy. We showed that the effects of KINVIS therapy with therapeutic exercise on upper limb motor functions were mediated by spasticity, and functional connectivity in the brain was also changed with the improvement of motor function after KINVIS therapy. Brain changes underlying behavioral changes need to be more examined, and the adaptation of stroke patients needs to be clarified in detail.

Funder

Japan Agency for Medical Research and Development

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

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