123952 20241125101126.0 doi 10.1177/15500594221120136 sideral 130176 ART-2023-130176 eng Asadi, Borhan The Effect of dry Needling in Chronic Stroke with a complex Network Approach: A Case Study 2023 Access copy available to the general public Unrestricted Background: Dry Needling (DN) has been demonstrated to be effective in improving sensorimotor function and spasticity in patients with chronic stroke. Electroencephalogram (EEG) has been used to analyze if DN has effects on the central nervous system of patients with stroke. There are no studies on how DN works in patients with chronic stroke based on EEG analysis using complex networks. Objective: The aim of this study was to assess how DN works when it is applied in a patient with stroke, using the graph theory. Methods: One session of DN was applied to the spastic brachialis muscle of a 62-year-old man with right hemiplegia after stroke. EEG was used to analyze the effects of DN following metrics that measure the topological configuration: 1) network density, 2) clustering coefficient, 3) average shortest path length, 4) betweenness centrality, and 5) small-worldness. Measurements were taken before and during DN. Results: An improvement of the brain activity was observed in this patient with stroke after the application of DN, which led to variations of local parameters of the brain network in the delta, theta and alpha bands, and inclined towards those of the healthy control bands. Conclusions: This case study showed the positive effects of DN on brain network of a patient with chronic stroke. info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 1.6 2023 CLINICAL NEUROLOGY 204 / 280 = 0.729 2023 Q3 T3 PSYCHIATRY 186 / 279 = 0.667 2023 Q3 T3 PSYCHOLOGY 59 / 92 = 0.641 2023 Q3 T2 NEUROIMAGING 12 / 15 = 0.8 2023 Q4 T3 NEUROSCIENCES 261 / 310 = 0.842 2023 Q4 T3 0.655 2023 Medicine (miscellaneous) 2023 Q2 Neurology (clinical) 2023 Q2 Neurology 2023 Q3 5.2 2023 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Fard, Kheirollah Rahsepar Ansari, Noureddin Nakhostin Marco, Alvaro Universidad de Zaragoza (orcid)0000-0002-7396-7840 Calvo, Sandra Universidad de Zaragoza (orcid)0000-0002-1674-7788 Herrero, Pablo Universidad de Zaragoza (orcid)0000-0002-9201-0120 5008 785 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Tecnología Electrónica 1006 413 Universidad de Zaragoza Dpto. Fisiatría y Enfermería Área Fisioterapia 54, 2 (2023), 179-188 Clin. EEG Neurosci. CLINICAL EEG AND NEUROSCIENCE 1550-0594 965407 http://zaguan.unizar.es/record/123952/files/texto_completo.pdf Postprint 1398786 http://zaguan.unizar.es/record/123952/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:123952 articulos driver 2024-11-22-11:57:41 ARTICLE