Diseño de un sistema embebido de clasificación de movimientos de los dedos de la mano, empleando electromiografía superficial en antebrazo Thesis

short description

  • Master's thesis

Thesis author

  • Sanabria-Solano, Alfredo-Jose

external tutor

  • Orjuela-Cañón, Alvaro David
  • Perdomo Charry, Oscar Julian

abstract

  • Surgery rooms are one of the environments where more security and control protocols are applied, even compared to environments such as aeronautics (Hales et al., 2008). One of the protocols of strict control in the surgery rooms of the world or even here in Colombia, is that of sterility. This protocol prevents surgical site infections, post-surgery complications, or infections that can result in even more complex treatments than the original ones to which the patient underwent in the first instance (Restrepo et al., 2011). One of the most frequently seen sources of contamination is due to the use of equipment outside the surgical field, such as computer equipment, image display equipment, among others. These systems provide information to the surgeon during the procedure, information that is vital at specific times for clinical decision making (Jimenez et al., 2017). Being able to interact with these systems, from the surgical environment, has become an imperative need both for the industry and for medical teams. In the search for solutions to this need, surface electromyography combined with CNN movement clasification has been found to be one of the best low-cost and easy-to-implement options (Tsuboi et al., 2017).

publication date

  • April 19, 2022 12:39 PM

keywords

  • CNN
  • EMG
  • Embebed System
  • Forearm
  • MLPC
  • MYO
  • Neural Network

Document Id

  • a69a769c-e893-4019-bf79-25cee2b5631e