Sistema semi-autônomo baseado em visão neuromórfica para controle de próteses mioelétricas

Detalhes bibliográficos
Ano de defesa: 2022
Autor(a) principal: Gouveia, Eber Lawrence Souza
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Uberlândia
Brasil
Programa de Pós-graduação em Engenharia Biomédica
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufu.br/handle/123456789/34778
http://doi.org/10.14393/ufu.di.2021.112
Resumo: In recent years, several studies have been looking for better ways for controlling upper-limb prostheses. However, current prosthesis control methods are still far from reaching the characteristics of the human limb, such as handling different degrees of freedom naturally and automatically. Furthermore, control systems based on the traditional Direct Control approach cannot provide many grasp types as the control complexity increases exponentially and consequently increases the required cognitive load of the user. Observing these limitations, this work presents a semi-autonomous control system, which uses a neuromorphic camera attached to the prosthesis for selecting the type of grasp and correct the angle of the prosthesis wrist according to the shape and angle of the desired object, respectively. Furthermore, the system can segment the desired object from the others contained in a single scene. Finally, two pickand-place experiments were carried out with volunteers, the first using the proposed semiautonomous control system and the second using a manual control system, based on switching movements through blocks. In addition, the NASA-TLX questionnaire was used to subjectively verify the level of workload during the experiments.