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Physical therapy assisted with a robot for motor volitional control in children with cerebral palsy: neurophysiological correlates

Grant number: 19/18409-9
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): January 20, 2020
Effective date (End): January 19, 2021
Field of knowledge:Physical Sciences and Mathematics - Physics
Principal Investigator:Gabriela Castellano
Grantee:Carlos Alberto Stefano Filho
Supervisor abroad: Eduardo Rocon de Lima
Home Institution: Instituto de Física Gleb Wataghin (IFGW). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Local de pesquisa : Consejo Superior de Investigaciones Científicas (CSIC), Spain  
Associated to the scholarship:16/22116-9 - Investigation of the neurofeedback technique using MRI, BP.DR


Cerebral palsy (CP) is an ensemble of disorders that develops early on childhood and imposes several limitations on gait, posture and on general motor activity. As an attempt to improve CP children's quality of life, orthopedic surgery, followed by physical therapy specific for motor rehabilitation, is a common procedure. Although CP is essentially a central nervous system (CNS) condition, most physical therapy approaches usually target only the peripheral nervous system (PNS). Therefore, a methodology integrating both the CNS and PNS could result in better motor recovery for these children. With these considerations, our main goal with this project is to advance in the understanding of the underlying neuronal mechanisms involved in motor volitional control of children submitted to an integrated CNS-PNS physical therapy. This integration is conceived through the CPWalker, a multi-modal robotic platform developed specifically for this end. One of the main goals of the CPWalker project is to validate and assess the feasibility of the platform usage in the clinical environment, for which, data from about 30 children post-CP surgery will be collected. The goal of the present project is to help CPWalker's validation and assessment through the analysis of the electroencephalography (EEG) data of the CPWalker. The analysis will encompass extracting relevant features for the task and investigating brain patterns for motor imagery and motor intention-related cortical structures, which will enable comparisons with our dataset of 30 healthy subjects that underwent motor imagery training in three conditions, acquired through our main PhD project.