Current open-source upper limb robotic prosthesis projects have limitations regarding the functionality they offer to users. Moreover, prostheses that succeed in this requirement are extremely expensive and involve a challenging interaction, which requires hard practice from the amputee to be able to control the device. To decrease the training time that upper limb amputees usually spend to control the prosthetic hands, and to simplify the interaction, we developed friendly human-machine interfaces based on hybrid Electromyography (EMG) with Inertial Measurement Unit (IMU) and Radio Frequency Identification (RFID). The results suggest that the use of these interfaces in prosthesis is beneficial since they do not demand a lot of effort from the user, meaning they will be able to control the prosthetic hands easily and without an extended period of training. Keywords— Robotics, Prosthetic Hands, Hybrid Human-Machine Interfaces, Electromyography Resumo— Projetos atuais livres de prótese de membro superior tem limitações quanto a funcionalidade que oferecem aos usuários. Além disso, as próteses que obtêm êxito nesse requisito possuem custo extremamente alto e envolvem uma interação desafiadora, que requer uma prática ŕıgida do amputado para controlar o dispositivo. Para diminuir o tempo de treinamento que os amputados de membros superiores costumam gastar para controlar as mãos protéticas e para simplificar a interação, desenvolvemos interfaces homem-máquina amigáveis baseadas em eletromiografia h́ıbrida (EMG) com Unidade de Medida Inercial (IMU) e Identificação por Rádio Frequência (RFID). Os resultados sugerem que o uso dessas interfaces em prótese é benéfico, uma vez que não exigem muito esforço do usuário, o que significa que eles serão capazes de controlar as mãos protéticas facilmente e sem um longo peŕıodo de treinamento. Palavras-chave— Robótica, Próteses de mão, Interface Homem-Máquina Hı́brida, Eletromiografia
[1]
Julio Fajardo,et al.
Galileo bionic hand: sEMG activated approaches for a multifunction upper-limb prosthetic
,
2015,
2015 IEEE Thirty Fifth Central American and Panama Convention (CONCAPAN XXXV).
[2]
Jhonatan Camacho Navarro,et al.
EMG-BASED SYSTEM FOR BASIC HAND MOVEMENT RECOGNITION
,
2012
.
[3]
Erik Scheme,et al.
Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use.
,
2011,
Journal of rehabilitation research and development.
[4]
Antonio Bicchi,et al.
Hands for dexterous manipulation and robust grasping: a difficult road toward simplicity
,
2000,
IEEE Trans. Robotics Autom..
[5]
Surya P. N. Singh,et al.
V-REP: A versatile and scalable robot simulation framework
,
2013,
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[6]
Timothy Bretl,et al.
Tact: Design and performance of an open-source, affordable, myoelectric prosthetic hand
,
2015,
2015 IEEE International Conference on Robotics and Automation (ICRA).