RESUMO
BACKGROUND: Depression and anxiety are non-motor symptoms of Parkinson's disease (PD). Physical exercise is a promising approach to reducing neuropsychological burden. We aimed to comprehensively synthesize evidence regarding the use of exercise for treating depression and anxiety symptoms in PD. METHODS: Systematic review and meta-analysis following PRISMA recommendations. Searches on PubMed, Cochrane Library, Scopus, Web of Science, Embase, and Physiotherapy Evidence Database (PEDro) was conducted. The random-effects model was employed for all analyses with the standardized mean difference as the effect estimate. RESULTS: Fifty records were retrieved, but only 17 studies met the criteria for the meta-analyses. A moderate to large effect was observed for depression (-.71 [95% CI = -.96 to -.46], 11 studies, 728 individuals), and a small to moderate effect for anxiety (-.39 [95% CI = -.65 to -.14], 6 studies, 241 individuals), when comparing exercise to non-exercise controls. Subgroup analysis revealed significant effects from aerobic (-.95 [95% CI = -1.60, -.31]), mind-body (-1.85 [95% CI = -2.63, -1.07]), and resistance modalities (-1.61 [95% CI = -2.40, -.83]) for depression, and from mind-body (-.67 [95% CI = -1.19 to -.15]) and resistance exercises (-1.00 [95% CI = -1.70 to -.30]) for anxiety. CONCLUSION: Physical exercise has a relevant clinical impact on depression and anxiety in PD. We discuss the level of the evidence, the methodological limitations of the studies, and give recommendations.
RESUMO
Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown promise in helping stroke patients regain lost motor functions. One potential avenue for increasing the understanding of how motor recovery occurs is to study brain activation during the movements that are targeted by therapy in healthy individuals. Functional Near-Infrared Spectroscopy (fNIRS) has emerged as a promising neuroimaging technique for examining neural underpinnings of motor function. This study aimed to investigate fNIRS neural correlates of complex lower limb movements in healthy subjects. Participants were asked to perform cycles of rest and movement for 6 min using a robotic device for motor rehabilitation. The task required coordinated knee and ankle joint movements to point to targets displayed on a computer screen. Two experimental conditions with different levels of movement assistance provided by the robot were explored. The results showed that the fNIRS protocol effectively detected brain regions associated with motor control during the task. Notably, all subjects exhibited greater activation in the contralateral premotor area during the no-assistance condition compared to the assisted condition. In conclusion, fNIRS appears to be a valuable approach for detecting changes in oxyhemoglobin concentration associated with multi-joint pointing movements of the lower limb. This research might contribute to the understanding of stroke motor recovery mechanisms and might pave the way for improved rehabilitation treatments for stroke patients. However, further research is needed to fully elucidate the potential of fNIRS in studying motor function and its applications in clinical settings.