Desenvolvimento de ferramentas para pesquisas em tecnologias assistivas baseadas em sinais biológicos

• Ano de defesa: 2015
• Autor(a) principal: Longo, Berthil Borges
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Biotecnologia; Centro de Ciências da Saúde; UFES; Programa de Pós-Graduação em Biotecnologia
• Palavras-chave em Português: Engenharia biomédica; Eletroencefalografia; Biotecnologia; 61
• Link de acesso: http://repositorio.ufes.br/handle/10/1351

New Assistive Technology (AT) tool has appeared lately. An example are the Virtual Environments (VE) which are important to new ATs development, that can aim to improve the life quality of people with permanent reduced mobility or to promote rehabilitation to people with temporary motor disability. Other tool that appeared some decades ago with computer development can also help in the treatment of motor disability persons, which are called Human Machine-Interface (HMI). Using it together with equipment that can acquire biological signals like Electromyography (EMG) and Electroencephalography (EEG), these tools behave as communication channels between humans and computers, different from the ones usually used. This opens a wide range of possibilities for its usage in the treatment and assistance of motor disability people, which EMG signals can be used to control robotic prosthesis, and EEG signal, when acquired from the motor cortex, can be used in neurorehabilitation. On the other hand, when these signals are captured from the occipital region, the EEG signals can be used to generate commands or used in other purposes. This work presents the development of new tools to be used in AT which uses biological signals. Three different VE where built to assist this kind of research. Furthermore, a commercial EEG equipment was adapted to be used with a HMI, which uses two of the built VE. As results, we have the successful use of the adapted EEG equipment with with SSVEP and motor imagery. Furthermore, the three developed AVs were successfully implemented, which are available for free download to be used in other TA projects.