Utilização de técnicas de realidade virtual na simulação de próteses de mão

• Ano de defesa: 2012
• Autor(a) principal: Mattioli, Fernando Eduardo Resende
• Orientador(a): Lamounier Júnior, Edgard Afonso
• Banca de defesa: Yamanaka, Keiji , Freitas, Carla Maria Dal Sasso
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia
• Programa de Pós-Graduação: Programa de Pós-graduação em Engenharia Elétrica
• Departamento: Engenharias
• País: BR
• Palavras-chave em Português: Realidade virtual; Redes neurais artificiais; Reabilitação humana; Redes neurais (Computação)
• Palavras-chave em Inglês: Virtual reality; Artificial neural networks; Human rehabilitation
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: https://repositorio.ufu.br/handle/123456789/14480; https://doi.org/10.14393/ufu.di.2012.22

In the past few years, computer-based training systems have been widely studied in the field of human rehabilitation. One of the cutting-edge technologies applied in this kind of system is Virtual Reality. In health applications, Virtual Reality presents itself as an appropriate tool to simulate training environments without exposing the patients to the real world associated risks. In particular, one application of Virtual Reality in human rehabilitation is in virtual prosthesis design. Virtual prosthetic devices have been used to reduce the great mental effort needed by patients fitted with myoelectric prosthesis, during the training stage. This effort is one of the main difficulties that lead patients to give up at this stage. In this paper, the application of Virtual Reality in a hand prosthesis training system is presented. To achieve this, the possibility of exploring Artificial Neural Networks in a real-time classification system is discussed. Also, a signal windowing algorithm and a communication architecture between the classification system and the virtual environment are presented. Finally, a prototype developed in order to investigate the application of the proposed system in a real-time processing and classification context is presented.