Objective: identify stabilometric changes before and after a program of proprioceptive training. Methods: a randomized controlled clinical trial was conducted with 18 subjects, mean age 20.6 ± 2.1 years of age, of both sexes, with a mean body mass index 23.3 ± 5.4 kg/m² that were evaluated in stabilometric platform before and after a program of proprioceptive training using the equipment and proprioceptive hard rocker, and divided into proprioception (n = 10) and control group (n = 8) group. The proprioceptive training consisted of 10 measures with one foot, knee in semiflexion for 30 seconds twice a week for five weeks using the rocker apparatus and proprioceptive disc. Results: D'Agostinotests were performed to test the normality, to which it was noted that the study sample was obtained normal behavior for both groups: proprioception and control, was used the Student t-test for observation the significance of p value (<0.05). At the end of the intervention subjects were reassessed at stabilometric platform on which it was observed that the proprioception group there was a significant reduction in body sway in relation to the control group (p = 0.002). Conclusion: the short time, with oneleg proprioceptive training has been shown to be effective for improving balance by reducing body sway.Key words: postural balance. exercise therapy. evaluation of results therapeutic interventions.-64 -Analysis after stabilometric proprioceptive exercises: a randomized controlled clinical study

Introdução: A Doença de Parkinson (DP) consiste uma afecção neurológica progressiva, caracterizada pela degeneração do sistema nervoso central. Entre as técnicas de tratamento utilizadas na DP, a realidade virtual (RV) é utilizada com o intuito de realizar simulações interativas em tempo real. Objetivo: O objetivo deste estudo foi verificar as técnicas mais utilizadas pelos pesquisadores atualmente na realidade virtual sobre a doença de Parkinson. Método: A revisão bibliográfica foi elaborada através da pesquisa nas bases Scielo, Bireme, Google scholar, PEdro e Cochrane, publicados no período de 2018 e 2019 com as palavras-chave virtual reality and Parkinson's disease. Resultados: Foram utilizados 7 artigos, onde o maior interesse dos pesquisadores foi saber se a RV é melhor do que o tratamento convencional e qual equipamento tem maior eficácia. Os métodos de avaliação foram variados, incluindo testes de marcha, mobilidade, cognição e qualidade de vida. Utilizaram amostra em média de 28,7 indivíduos com tempo de tratamento médio de 12,6 sessões. A técnica de realidade virtual foi capaz de obter 85% de eficácia para os pacientes com DP. Conclusão: A realidade virtual é um conceituado método de tratamento para a doença de Parkinson. Sugere-se a realização de pesquisas sobre a resposta da doença no momento em que o paciente será inserido ao ambiente real.

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Purpose Functional electrical stimulation (FES) is a method of activating paralyzed muscles. During FES application, fast muscle fatigue can occur (the inability of stimulated muscles to generate force). Therefore, it is beneficial to estimate the muscle fatigue for FES closed-loop control for walking to prevent unexpected muscle collapse and adapt the FES strategy in real time. Mechanomyography (MMG) is a noninvasive technique for registering myofiber vibrations, representing an ideal candidate for the provision of feedback. The hypothesis was that MMG signals could effectively detect muscle fatigue and, thus, provide feedback. Methods We tested this hypothesis by analyzing the wavelet transform of signals from an MMG sensor positioned over the rectus femoris muscle during electrically evoked contractions in subjects with spinal cord injury (SCI). The signals were collected from a total of 24 lower limb muscles. We investigated both legs of 15 participants with spinal cord injury (male, YOA = 27.13 ± 5.05, M = 75.8 ± 10.35 kg, and H = 1.78 ± 0.07 m, American Spinal Injury Impairment Scale (AIS) A and B). All MMG signals were analyzed in 12 frequency bands from 5 to 53 Hz. Results We found different trends in the magnitudes in different frequency bands. The magnitude decreased in 13, 16, 20, 25, and 35 Hz bands in correlation with fatigue. The greatest statistical difference was found at 20 Hz and 25 Hz. Conclusion This result suggests that processed MMG signals indicate muscle fatigue and can, thus, be used as the feedback in FES systems.